Developmental Psychopathology and Longitudinal Methods

doi:10.1017/9781316995808.018

Part IV - Developmental Psychopathology and Longitudinal Methods

Published online by Cambridge University Press: 23 March 2020

Edited by

Aidan G. C. Wright and

Michael N. Hallquist

Show author details

Aidan G. C. Wright: Affiliation:
University of Pittsburgh
Michael N. Hallquist: Affiliation:
Pennsylvania State University

Book contents

Get access

Summary

A summary is not available for this content so a preview has been provided. Please use the Get access link above for information on how to access this content.

Image of the first page of this content. For PDF version, please use the ‘Save PDF’ preceeding this image.'

Type: Chapter
Information: The Cambridge Handbook of Research Methods in Clinical Psychology , pp. 191 - 264

DOI: https://doi.org/10.1017/9781316995808.018 [Opens in a new window]

Publisher: Cambridge University Press

Print publication year: 2020

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

American Psychiatric Association (APA). (2013). Diagnostic and Statistical Manual of Mental Disorders (5th edn.). Arlington, VA: American Psychiatric Publishing.Google Scholar

Anacker, C., O’Donnell, K. J., & Meaney, M. J. (2014). Early Life Adversity and the Epigenetic Programming of Hypothalamic-Pituitary-Adrenal Function. Dialogues of Clinical Neuroscience, 16(3) 321‒333.CrossRef Google Scholar PubMed

Beauchaine, T. P. & Klein, D. N. (2017). Classifying Psychopathology: The DSM, Empirically Based Taxonomies, and the Research Domain Criteria. In Beauchaine, T. P. & Hinshaw, S. P. (Eds.), Child and Adolescent Psychopathology (3rd edn., pp. 33‒67). Hoboken, NJ: John Wiley & SonsGoogle Scholar

Cairns, R.B. (1983). The Emergence of Developmental Psychology. In Kessen, W. (Ed.), Carmichael’s Handbook of Child Psychology: Vol. I. History, Theory, and Methods (4th edn., pp. 41‒102). New York: Wiley.Google Scholar

Charney, D. (2004). Psychobiological Mechanisms of Resilience and Vulnerability: Implications for Successful Adaptation to Extreme Stress. American Journal of Psychiatry, 161, 195–216.Google Scholar

Ciaranello, R., Aimi, J., Dean, R. S., Morilak, D., Porteus, M. H., & Cicchetti, D. (1995). Fundamentals of Molecular Neurobiology. In Cicchetti, D. & Cohen, D. J. (Eds.), Developmental Psychopathology: Theory and Method (Vol. 1, pp. 109‒160). New York: Wiley.Google Scholar

Cicchetti, D. (1984). The Emergence of Developmental Psychopathology. Child Development, 55(1), 1‒7.Google Scholar

Cicchetti, D. (1990). A Historical Perspective on the Discipline of Developmental Psychopathology. In Rolf, J., Masten, A., Cicchetti, D., Nuechterlein, K., & Weintraub, S. (Eds.), Risk and Protective Factors in the Development of Psychopathology (pp. 2‒28). New York: Cambridge University Press.Google Scholar

Cicchetti, D. (1993). Developmental Psychopathology: Reactions, Reflections, Projections. Developmental Review, 13, 471‒502.Google Scholar

Cicchetti, D. (2002). The Impact of Social Experience on Neurobiological Systems: Illustration from a Constructivist View of Child Maltreatment. Cognitive Development, 17, 1407–1428.CrossRef Google Scholar

Cicchetti, D. (2006). Development and Psychopathology. In Cicchetti, D. & Cohen, D. J. (Eds.), Developmental Psychopathology (Vol. 1, 2nd edn., pp. 1‒23). New York: Wiley.Google Scholar

Cicchetti, D. (2013). Annual Research Review: Resilient Functioning in Maltreated Children ‒ Past, Present, and Future Perspectives. Journal of Child Psychology and Psychiatry, 54, 402‒422.Google Scholar

Cicchetti, D. (Eds.) (2017). Biological and Behavioral Effects of Early Adversity on Multiple Levels Of Development. Development and Psychopathology, 29(5) [Special Issue], 1517–1986.Google Scholar

Cicchetti, D. (2018). A Multilevel Developmental Approach to the Prevention of Psychopathology in Children and Adolescents. In Butcher, J. N., Hooley, J., & Kendall, P. D. (Eds.), APA Handbook of Psychopathology (pp. 37‒53). Washington, DC: American Psychological Association Books.Google Scholar

Cicchetti, D., & Cannon, T. D. (1999). Neurodevelopmental Processes in the Ontogenesis and Epigenesis of Psychopathology. Development and Psychopathology, 11, 375‒393.CrossRef Google Scholar PubMed

Cicchetti, D., & Curtis, W. J. (2006). The Developing Brain and Neural Plasticity: Implications for Normality, Psychopathology, and Resilience. In Cicchetti, D. & Cohen, D. J. (Eds.), Developmental Psychopathology: Developmental Neuroscience (Vol. 2, 2nd edn., pp. 1–64). New York: Wiley.Google Scholar

Cicchetti, D., & Gunnar, M. R. (2008). Integrating Biological Processes into the Design and Evaluation of Preventive Interventions. Development and Psychopathology, 20(3), 737–743.Google Scholar

Cicchetti, D., & Garmezy, N. (1993). Prospects and Promises in the Study of Resilience. Development and Psychopathology, 5, 497‒502.Google Scholar

Cicchetti, D., & Hinshaw, S. P. (Eds.) (2002). Editorial: Prevention and Intervention Science: Contributions to Developmental Theory. Development and Psychopathology, 14(4), 667–671.Google Scholar

Cicchetti, D., & Pogge-Hesse, P. (1982). Possible Contributions of the Study of Organically Retarded Persons to Developmental Theory. In Zigler, E. & Balla, D. (Eds.), Mental Retardation: The Developmental-Difference Controversy (pp. 277‒318). Hillsdale, NJ: Lawrence Erlbaum Associates.Google Scholar

Cicchetti, D., & Rogosch, F. A. (1996). Equifinality and Multifinality in Developmental Psychopathology. Development and Psychopathology, 8, 597‒600.Google Scholar

Cicchetti, D., & Rogosch, F. A. (1997). The Role of Self-Organization in the Promotion of Resilience in Maltreated Children. Development and Psychopathology, 9, 797‒815.CrossRef Google Scholar PubMed

Cicchetti, D., & Schneider-Rosen, K. (1986). An Organizational Approach to Childhood Depression. In Rutter, M., Izard, C., & Read, P. (Eds.), Depression in Young People, Clinical and Developmental Perspectives (pp. 71‒134). New York: Guilford.Google Scholar

Cicchetti, D., & Sroufe, L. A. (1978). An Organizational View of Affect: Illustration from the Study of Down’s Syndrome Infants. In Lewis, M. & Rosenblum, L. (Eds.), The Development of Affect (pp. 309‒350). New York: Plenum Press.Google Scholar

Cicchetti, D., & Sroufe, L. A. (2000). The Past as Prologue to the Future: The Times, They’ve Been a Changin’. Development and Psychopathology, 12, 255‒264.Google Scholar

Cicchetti, D., & Toth, S. L. (2016). Child Maltreatment and Developmental Psychopathology: A Multilevel Perspective. In Cicchetti, D. (Ed.), Developmental Psychopathology (3rd edn., Vol. 3, Maladaptation and Psychopathology, pp. 457‒512). New York: Wiley.Google Scholar

Cicchetti, D., & Toth, S. L. (2017). Using the Science of Developmental Psychopathology to Inform Child and Adolescent Psychotherapy. In Kazdin, A. E. & Weisz, J. R. (Eds.). Evidence-Based Psychotherapies for Children and Adolescents (pp. 484‒500). New York: The Guilford Press.Google Scholar

Cicchetti, D., & Tucker, D. (1994). Development and Self-Regulatory Structures of the Mind. Development and Psychopathology, 6, 533‒549.Google Scholar

DeBellis, M. D. (2001). Developmental Traumatology: The Psychobiological Development of Maltreated Children and Its Implications for Research, Treatment, and Policy. Development and Psychopathology, 13, 539‒564.Google Scholar

Demers, L., Jedd-McKenzie, K., Hunt, R. H., Cicchetti, D., Cowell, R. A., Rogosch, F. A., … Thomas, K. M. (2018). Separable Effects of Maltreatment and Adult Functioning on Amygdala Connectivity during Emotion Processing. Biological Psychiatry: Cognitive Neuroscience and Neuroimaging, 3(2), 116‒124.Google Scholar

Egeland, B., & Carlson, E., & Sroufe, L. A. (1993). Resilience as Process. Development and Psychopathology, 5(4), 517‒528.Google Scholar

Eisenberg, L. (1995). The Social Construction of the Human Brain. American Journal of Psychiatry, 152, 1563‒1575.Google Scholar

Erikson, E. H., (1950). Childhood and Society. New York: Norton.Google Scholar

Farah, M. J. (2017). The Neuroscience of Socioeconomic Status: Correlates, Causes, and Consequences. Neuron, 96(1), 56‒71.CrossRef Google Scholar PubMed

Fishbein, H. D. (1976). Evolution, Development, and Children’s Learning. Pacific Palisades, CA: Goodyear Publishing.Google Scholar

Gottlieb, G. (1976). Conceptions of Prenatal Development: Behavioral Embryology. Psychological Review, 83(3), 214‒234.Google Scholar

Gottlieb, G. (1983). Psychobiological Approach to Developmental Issues. In Haith, M. M. & Campos, J (Eds.), Handbook of Child Psychology: Infancy and Biological Bases (Vol. 2, pp. 1‒26). New York: Wiley.Google Scholar

Gottlieb, G. (1991). Behavioral Pathway to Evolutionary Change. Rivista Di Biologia, 84(3), 385‒409.Google Scholar

Gottlieb, G. (1992). Individual Development and Evolution: The Genesis of Novel Behavior. New York: Oxford University Press.Google Scholar

Gottlieb, G. (1998). The Significance of Biology for Human Development: A Developmental Psychobiological Systems View. In Damon, W. & Lerner, R. M. (Eds.), Handbook of Child Psychology (Vol. 1, 5th edn., pp. 233–273). New York: Wiley.Google Scholar

Gottlieb, G. (2001). The Relevance of Developmental-Psychobiological Metatheory to Developmental Neuropsychology. Developmental Neuropsychology, 19(1), 1–9.Google Scholar

Gottlieb, G. (2007). Probabilistic Epigenesis. Developmental Science, 10, 1–11.CrossRef Google Scholar PubMed

Greenough, W., Black, J., & Wallace, C. (1987). Experience and Brain Development. Child Development, 58, 539‒559.Google Scholar

Gunnar, M. R., & Quevedo, K. (2007). The Neurobiology of Stress and Development. Annual Review of Psychology, 58, 145–173.Google Scholar

Hanson, D., & Gottesman, I. I. (2007). Choreographing Genetic, Epigenetic, and Stochastic Steps in the Dances of Developmental Psychopathology. In Masten, A. S. (Ed.), Multilevel Dynamics in Developmental Psychopathology: Pathways to the Future: The Minnesota Symposia on Child Psychology (Vol. 34, pp. 27‒44). Mahwah, NJ: Lawrence Erlbaum Associates.Google Scholar

Heckman, J. J. (2006). Skill Formation and the Economics of Investing in Disadvantaged Children. Science, 312, 1900–1902.Google Scholar

Howe, G. W., Reiss, D., & Yuh, J. (2002). Can Prevention Trials Test Theories of Etiology? Development and Psychopathology, 14, 673‒694.Google Scholar

Institute of Medicine. (1994). Reducing Risks for Mental Disorders: Frontiers for Preventive Intervention Research. In Mrazek, P. J. & Haggerty, R. J. (Eds.), Committee on Prevention of Mental Disorders, Division of Biobehavorial Sciences and Mental Disorders. Washington, DC: National Academies Press.Google Scholar

Jedd, K., Hunt, R. H., Cicchetti, D., Hunt, E., Rogosch, F., Toth, S., & Thomas, K. M. (2015). Long-term Consequences of Childhood Maltreatment: Altered Amygdala Functional Connectivity. Development and Psychopathology, 27(4pt2), 1577‒1589.Google Scholar

Kempermann, G. (2006). Adult Neurogenesis: Stem Cells and Neuronal Development in the Adult Brain. New York: Oxford University Press.Google Scholar

Kemperman, G., van Praag, H., & Gage, F. H. (2000). Activity-Dependent Regulation of Neuronal Plasticity and Self-Repair. Progress in Brain Research, 127, 35‒48.Google Scholar

Kohlberg, L., LaCrosse, J., & Ricks, D. (1972). The Predictability of Adult Mental Health from Childhood Behavior. In Wolman, B. B. (Ed.), Manual of Child Psychopathology (pp. 1217–1284). New York: McGraw-Hill.Google Scholar

Kraemer, H. C., Kazdin, A. E., Offord, D. R., Kessler, R. C., Jensen, P. S., & Kupfer, D. J. (1997). Coming to Terms with the Terms of Risk. Archives of General Psychiatry, 54, 337–343.CrossRef Google Scholar PubMed

Krueger, R. F., Markon, K. E., Patrick, C. J., & Iacono, W. G. (2005). Externalizing Psychopathology in Adulthood: A Dimensional-Spectrum Conceptualization and Its Implications for DSM-5. Journal of Abnormal Psychology, 114, 537‒550.Google Scholar

Leve, L. D., & Cicchetti, D. (2016). Longitudinal Transactional Models of Development and Psychopathology. Development and Psychopathology, 28(3), 621‒622.Google Scholar

Luthar, S. S., & Cicchetti, D. (2000). The Construct of Resilience: Implications for Intervention and Social Policy. Development and Psychopathology, 12, 857‒885.Google Scholar

Luthar, S. S., Cicchetti, D., & Becker, B. (2000). The Construct of Resilience: A Critical Evaluation and Guidelines for Future Work. Child Development, 71, 543‒562.Google Scholar

MacKinnon, D. P. (2008). Introduction to Statistical Mediation Analysis. Mahwah, NJ: Lawrence Erlbaum.Google Scholar

Masten, A.S. (2006). Developmental Psychopathology: Pathways to the Future. International Journal of Behavior Disorders, 30, 47–54.CrossRef Google Scholar

Masten, A. S. (2014). Ordinary Magic: Resilience in Development. New York: Guilford.Google Scholar

Masten, A. S., Burt, K. B., & Coatsworth, J. D. (2006). Competence and Psychopathology in Development. In Cicchetti, D. & Cohen, D. J. (Eds.), Developmental Psychopathology (Vol. 3, 2nd edn., pp. 696–738). Hoboken, NJ: WileyGoogle Scholar

Masten, A. S., & Cicchetti, D. (2010). Developmental Cascades. Developmental Cascades [Special Issue, Part 1], Development and Psychopathology, 22(3), 491‒495.Google Scholar

Masten, A. S. & Cicchetti, D. (2016). Resilience in Development: Progress and Transformation. In Cicchetti, D. (Ed.), Developmental Psychopathology (Vol. 4, Risk, Resilience, and Intervention, 3rd edn., pp. 271‒333). New York: Wiley.Google Scholar

Masten, A. S., & Coatsworth, J.D. (1998). The Development of Competence in Favorable and Unfavorable Environments: Lessons from Research on Successful Children. American Psychologist, 53, 205–220.Google Scholar

Masten, A. S., Long, J. D., Kuo, S. I.-C., McCormick, C. M., & Desjardins, C. D. (2009). Developmental Models of Strategic Intervention. European Journal of Developmental Science, 3, 282–291.Google Scholar

Masten, A. S., & Wright, M. O. (2009). Resilience over the Lifespan: Developmental Perspectives on Resistance, Recovery, and Transformation. In Reich, J. W., Zautra, A. J., & Hall, J. S. (Eds.), Handbook of Adult Resilience (pp. 213–237). New York: Guilford PressGoogle Scholar

McCrory, E., De Brito, S. A., & Viding, E. (2010). Research Review: The Neurobiology and Genetics of Maltreatment and Adversity. Journal of Child Psychology and Psychiatry, 51, 1079‒1095.CrossRef Google Scholar PubMed

Meaney, M. J. (2010). Epigenetics and the Biological Definition of Gene x Environment Interactions. Child Development, 81(1), 41‒79.CrossRef Google Scholar PubMed

Moffitt, T. E. (2005). The New Look of Behavioral Genetics in Developmental Psychopathology: Gene-Environment Interplay in Antisocial Behaviors. Psychological Bulletin, 131(4), 533‒554.Google Scholar

Paus, T., Keshavan, M., Giedd, J. N. (2008). Why Do Many Psychiatric Disorders Emerge during Adolescence? National Review of Neuroscience, 9(12), 947‒957.Google Scholar

Preacher, K. J., & Hayes, A. F. (2008). Asymptotic and Resampling Strategies for Assessing and Comparing Indirect Effects in Multiple Mediator Models. Behavior Research Methods, 40(3), 879‒891.Google Scholar

Rakic, P. (1988). Specification of Cerebral Cortical Areas. Science, 241, 170‒176.Google Scholar

Reynolds, A. J., & Temple, J. A. (2006). Economic Benefits of Investments in Preschool Education. In Zigler, E., Gilliam, W., & Jones, S. (Eds.), A Vision for Universal Prekindergarten (pp. 37–68). New York: Cambridge University Press.Google Scholar

Roisman, G. I., Masten, A. S., Coatsworth, J. D., & Tellegen, A. (2004). Salient and Emerging Developmental Tasks in the Transition to Adulthood. Child Development, 75, 1–11.CrossRef Google Scholar PubMed

Rutter, M. (1986). Child Psychiatry: The Interface between Clinical and Developmental Research. Psychological Medicine, 16, 151‒160.Google Scholar

Rutter, M. (1988). Epidemiological Approaches to Developmental Psychopathology. Archives of General Psychiatry, 45(5), 486‒495.Google Scholar

Rutter, M., & Garmezy, N. (1983). Developmental Psychopathology. In Hetherington, E. M. (Ed.), Mussen’s Handbook of Child Psychology: Vol. 4 Socialization, Personality, and Social Development (4th edn., pp. 775–911). New York: Wiley.Google Scholar

Sameroff, A. J. (2000). Developmental Systems and Psychopathology. Development and Psychopathology, 12, 297‒312.Google Scholar

Sameroff, A. J., & Chandler, M. J. (1975). Reproductive Risk and the Continuum of Caretaking Causality. In Horowitz, F. D. (Ed.), Review of Child Development Research (Vol. 4, pp. 187‒244). Chicago: University of Chicago Press.Google Scholar

Scarr, S., & McCarney, K. (1983). How People Make Their Own Environments: A Theory of Genotype-Environment Effects. Child Development, 54, 424‒435.Google Scholar

Shonkoff, J. P., Boyce, W. T., & McEwen, B. S. (2009). Neuroscience, Molecular Biology, and the Childhood Roots of Health Disparities: Building a New Framework for Health Promotion and Disease Prevention. Journal of the American Medical Association, 301, 2252–2259.Google Scholar

Sroufe, L. A. (1979). The Coherence of Individual Development: Early Care, Attachment, and Subsequent Developmental Issues. American Psychologist, 34, 834–841.Google Scholar

Sroufe, L. A. (1986). Bowlby’s Contribution to Psychoanalytic Theory and Developmental Psychopathology. Journal of Child Psychology and Psychiatry, 27, 841‒849.Google Scholar

Sroufe, L. A. (1989). Pathways to Adaptation and Maladaptation: Psychopathology as Developmental Deviation. In Cicchetti, D. (Ed.), Rochester Symposia on Developmental Psychopathology (Vol. 1, pp. 13‒40). Hillsdale, NJ: Erlbaum.Google Scholar

Sroufe, L. A. (1990). An Organizational Perspective on the Self. In Cicchetti, D. & Beeghly, M. (Eds.), The Self in Transition: Infancy to Childhood (pp. 281–307). Chicago, IL: University of Chicago Press.Google Scholar

Sroufe, L. A. (2007). The Place of Development in Developmental Psychopathology. In Masten, A. (Ed.), Multilevel Dynamics in Developmental Psychopathology: Pathways to the Future: The Minnesota Symposia on Child Psychology (Vol. 34, pp. 285‒299). Mahwah, NJ: Erlbaum.Google Scholar

Sroufe, L. A., (2013). The Promise of Developmental Psychopathology: Past and Present. Development and Psychopathology, 25, 1215‒1224.Google Scholar

Sroufe, L. A., Egeland, B., & Kreutzer, T. (1990). The Fate of Early Experience Following Developmental Change: Longitudinal Approaches to Individual Adaptation in Childhood. Child Development, 61, 1363‒1373.Google Scholar

Sroufe, L. A., & Jacobvitz, D. (1989). Diverging Pathways, Developmental Transformations, Multiple Etiologies and the Problem of Continuity in Development. Human Development, 32(3‒4), 196‒203.Google Scholar

Sroufe, L. A., & Rutter, M. (1984). The Domain of Developmental Psychopathology. Child Development, 55, 17‒29.CrossRef Google Scholar PubMed

Thelen, E., & Smith, L. B. (1998). Dynamic Systems Theories. In Damon, W. & Lerner, R. (Eds.), Theoretical Models of Human Development: Vol. 1 Handbook of Child Psychology (pp. 563‒634). New York: Wiley.Google Scholar

Thomas, K., & Cicchetti, D. (Eds.) (2008). Imaging Brain Systems in Normality and Psychopathology [Special Issue]. Development and Psychopathology, 20(4), 1023‒1349.Google Scholar

Toth, S. L., Gravener-Davis, J. A., Guild, D. J., & Cicchetti, D. (2013). Relational Interventions for Child Maltreatment: Past, Present, & Future Perspectives. Development and Psychopathology, 25(4pt2), 1601‒1617.Google Scholar

Von Bertalanffy, L. (1968). General System Theory: Foundations, Development, Applications. New York: Braziller.Google Scholar

Waddington, C. H. (1957). The Strategy of Genes. London: Allen & Unwin.Google Scholar

Waddington, C. H. (1966). Principles of Development and Differentiation. New York: Macmillan.Google Scholar

Waters, E., & Sroufe, L. A. (1983). Competence as a Developmental Construct. Developmental Review, 3, 79–97.Google Scholar

Weiss, P. A. (1969). Principles of Development: A Text in Experimental Embryology. New York: Hafner Publishing.Google Scholar

Weisz, J. R. & Kazdin, A. E. (Eds.) (2017). Evidence-Based Psychotherapies for Children and Adolescents. New York: Guilford Press.Google Scholar

Werner, H. (1948). Comparative Psychology of Mental Development. New York: International Universities Press.Google Scholar

Zigler, E., & Glick, M. (1986). A Developmental Approach to Adult Psychopathology. New York: Wiley.Google Scholar

References

Achenbach, T. M. (1993). Taxonomy and Comorbidity of Conduct Problems: Evidence from Empirically Based Approaches. Development and Psychopathology, 5(1–2), 51‒64.Google Scholar

Biro, F. M., & Deardorff, J. (2013). Identifying Opportunities for Cancer Prevention during Preadolescence and Adolescence: Puberty as a Window of Susceptibility. Journal of Adolescent Health, 52(5), S15‒S20.Google Scholar

Beltz, A. M., & Berenbaum, S. A. (2013). Cognitive Effects of Variations in Pubertal Timing: Is Puberty a Period of Brain Organization for Human Sex-Typed Cognition? Hormones and Behavior, 63(5), 823‒828.Google Scholar

Beltz, A., Acharya, R., Graber, J. A., Nixon, S. J., & Lynne, S. D. (2017). Puberty Influences Reward-Related Neural Connectivity: Girls with Early versus Typical Maturation. Paper presented as part of a symposium at the Society for Research in Child Development Biennial Meeting, Austin, TX, April 6‒8.Google Scholar

Braveman, P., Egerter, S., & Williams, D. R. (2011). The Social Determinants of Health: Coming of Age. Annual Review of Public Health, 32, 381‒398.Google Scholar

Bronfenbrenner, U. (2009). The Ecology of Human Development. Cambridge, MA: Harvard University Press.Google Scholar

Brooks-Gunn, J., Petersen, A. C., & Eichorn, D. (1985). The Study of Maturational Timing Effects in Adolescence. Journal of Youth and Adolescence, 14(3), 149‒161.Google Scholar

Byrne, M. L., Whittle, S., Vijayakumar, N., Dennison, M., Simmons, J. G., & Allen, N. B. (2017). A Systematic Review of Adrenarche as a Sensitive Period in Neurobiological Development and Mental Health. Developmental Cognitive Neuroscience, 25, 12–28.Google Scholar

Caspi, A., Houts, R. M., Belsky, D. W., Goldman-Mellor, S. J., Harrington, H., Israel, S., … Moffitt, T. E. (2014). The P Factor: One General Psychopathology Factor in the Structure of Psychiatric Disorders? Clinical Psychological Science, 2(2), 119‒137.Google Scholar

Center for Behavioral Health Statistics and Quality. (2017). 2016 National Survey on Drug Use and Health: Detailed Tables. Substance Abuse and Mental Health Services Administration, Rockville, MD.Google Scholar

Cerdá, M., Sarvet, A. L., Wall, M., Feng, T., Keyes, K. M., Galea, S., & Hasin, D. S. (2018). Medical Marijuana Laws and Adolescent Use of Marijuana and Other Substances: Alcohol, Cigarettes, Prescription Drugs, and Other Illicit Drugs. Drug and Alcohol Dependence, 183, 62–68.Google Scholar

Charalampopoulos, D., McLoughlin, A., Elks, C. E., & Ong, K. K. (2014). Age at Menarche and Risks of All-Cause and Cardiovascular Death: A Systematic Review and Meta-Analysis. American Journal of Epidemiology, 180(1), 29–40.Google Scholar

Chavarro, J. E., Watkins, D. J., Afeiche, M. C., Zhang, Z., Sánchez, B. N., Cantonwine, D., … Peterson, K. E. (2017). Validity of Self-Assessed Sexual Maturation against Physician Assessments and Hormone Levels. Journal of Pediatrics, 186, 172‒178.Google Scholar

Choo, E. K., Benz, M., Zaller, N., Warren, O., Rising, K. L., & McConnell, K. J. (2014). The Impact of State Medical Marijuana Legislation on Adolescent Marijuana Use. Journal of Adolescent Health, 55, 160–166.Google Scholar

Chumlea, W. C., Schubert, C. M., Roche, A. F., Kulin, H. E., Lee, P. A., Himes, J. H., & Sun, S. S. (2003). Age at Menarche and Racial Comparisons in US Girls. Pediatrics, 111(1), 110–113.Google Scholar

Chow, J. C. C., Jaffee, K., & Snowden, L. (2003). Racial/Ethnic Disparities in the Use of Mental Health Services in Poverty Areas. American Journal of Public Health, 93(5), 792‒797.Google Scholar

Compas, B. E., & Oppedisano, G. ( 2000 ). Mixed Anxiety/Depression in Childhood and Adolescence. In Sameroff, A. J., Lewis, M., & Miller, S. M. (Eds.), Handbook of Developmental Psychopathology (2nd edn., pp. 531–548). New York: Plenum Press.Google Scholar

Crone, E. A., & Dahl, R. E. (2012). Understanding Adolescence as a Period of Social-Affective Engagement and Goal Flexibility. Nature Reviews. Neuroscience, 13(9), 636‒650.Google Scholar

Dimick, J. B., & Ryan, A. M. (2014). Methods for Evaluating Changes in Health Care Policy: The Difference-in-Differences Approach. JAMA Guide to Statistics and Methods, 312(22), 2401–2402.Google Scholar

Dorn, L. D., Susman, E. J., & Ponirakis, A. (2003). Pubertal Timing and Adolescent Adjustment and Behavior: Conclusions Vary by Rater. Journal of Youth and Adolescence, 32(3), 157–167.Google Scholar

Dorn, L. D., & Biro, F. M. (2011). Puberty and Its Measurement: A Decade in Review. Journal of Research on Adolescence, 21(1), 180‒195.Google Scholar

Dubas, J. S., Graber, J. A., & Petersen, A. C. (1991). A Longitudinal Investigation of Adolescents’ Changing Perceptions of Pubertal Timing. Developmental Psychology, 27(4), 580‒586.Google Scholar

Egger, H. L., & Angold, A. (2006). Common Emotional and Behavioral Disorders in Preschool Children: Presentation, Nosology, and Epidemiology. Journal of Child Psychology and Psychiatry, 47, 313‒337.Google Scholar

Ellis, B. J., Boyce, W. T., Belsky, J., Bakermans-Kranenburg, M. J., & Van IJzendoorn, M. H. (2011). Differential Susceptibility to the Environment: An Evolutionary-Neurodevelopmental Theory. Development and Psychopathology, 23(1), 7‒28.Google Scholar

Epstein, S. (1994). Integration of the Cognitive and the Psychodynamic Unconscious. American Psychologist, 49(8), 709–724.Google Scholar

Evans, J. S. B. T, & Stanovich, K. E. (2013). Dual-Process Theories of Higher Cognition: Advancing the Debate. Perspectives on Psychological Science, 8(3), 223–241.CrossRef Google Scholar PubMed

Floyd, F. J., & Stein, T. S. (2002). Sexual Orientation Identity Formation among Gay, Lesbian, and Bisexual Youths: Multiple Patterns of Milestone Experiences. Journal of Research on Adolescence, 12(2), 167‒191.Google Scholar

Freedman, D. S., Khan, L. K., Serdula, M. K., Dietz, W. H., Srinivasan, S. R., & Berenson, G. S. (2003). The Relation of Menarcheal Age to Obesity in Childhood and Adulthood: The Bogalusa Heart Study. BMC Pediatrics, 3(1), 3‒11.Google Scholar

French, B., & Heagerty, P. J. (2008). Analysis of Longitudinal Data to Evaluate a Policy Change. Statistics in Medicine, 27, 5005–5025.Google Scholar

Ge, X., & Natsuaki, M. N. (2009). In Search of Explanations for Early Pubertal Timing Effects on Developmental Psychopathology. Current Directions in Psychological Science, 18(6), 327‒331.Google Scholar

Graber, J. A. (2013). Pubertal Timing and the Development of Psychopathology in Adolescence and Beyond. Hormones and Behavior, 64(2), 262‒269.Google Scholar

Graber, J. A., & Sontag, L. M. (2009). Internalizing Problems during Adolescence. In Lerner, R. M. & Steinberg, L. (Eds.), Handbook of Adolescent Psychology: Individual Bases of Adolescent Development (pp. 642‒682). Hoboken, NJ: Wiley.Google Scholar

Graber, J. A., Petersen, A. C., & Brooks-Gunn, J. (1996). Pubertal Processes: Methods, Measures, and Models. In Graber, J. A., Brooks-Gunn, J., & Petersen, A. C. (Eds.), Transition through Adolescence: Interpersonal Domains and Context (pp. 23–54). Mahwah, NJ: Erlbaum.Google Scholar

Harper, S., Strumpf, E. C., & Kaufman, J. S. (2012). Do Medical Marijuana Laws Increase Marijuana Use? Replication Study and Extension. Annals of Epidemiology, 22(3), 207–212.Google Scholar

Harris, K. M., Gordon-Larsen, P., Chantala, K., & Udry, J. R. (2006). Longitudinal Trends in Race/Ethnic Disparities in Leading Health Indicators from Adolescence to Young Adulthood. Archives of Pediatrics & Adolescent Medicine, 160(1), 74‒81.Google Scholar

Hasin, D. S., Wall, M., Keyes, K. M., Cerdá, M., Schulenberg, J., O’Malley, P. M., … Feng, T. (2015). Medical Marijuana Laws and Adolescent Marijuana Use in the USA from 1991 to 2014: Results from Annual, Repeated Cross-Sectional Surveys. The Lancet, 2(7), 601–608.Google Scholar

Herman-Giddens, M. E., Slora, E. J., Wasserman, R. C., Bourdony, C. J., Bhapkar, M. V., Koch, G. G., & Hasemeier, C. M. (1997). Secondary Sexual Characteristics and Menses in Young Girls Seen in Office Practice: A Study from the Pediatric Research in Office Settings Network. Pediatrics, 99(4), 505‒512.Google Scholar

Herman-Giddens, M. E., Steffes, J., Harris, D., Slora, E., Hussey, M., Dowshen, S. A., … Reiter, E. O. (2012). Secondary Sexual Characteristics in Boys: Data from the Pediatric Research in Office Settings Network. Pediatrics, 130(5), e1058‒e1068.Google Scholar

Hottes, T. S., Bogaert, L., Rhodes, A. E., Brennan, D. J., & Gesink, D. (2016). Lifetime Prevalence of Suicide Attempts among Sexual Minority Adults by Study Sampling Strategies: A Systematic Review and Meta-Analysis. American Journal of Public Health, 106(5), e1‒e12.Google Scholar

Insel, T. R. (2009). Translating Scientific Opportunity into Public Health Impact: A Strategic Plan for Research on Mental Illness. Archives of General Psychiatry, 66(2), 128‒133.Google Scholar

Katz-Wise, S. L., Rosario, M., Calzo, J. P., Scherer, E. A., Sarda, V., & Austin, S. B. (2017). Endorsement and Timing of Sexual Orientation Developmental Milestones among Sexual Minority Young Adults in the Growing Up Today Study. Journal of Sex Research, 54(2), 172‒185.Google Scholar

King, M., Semlyen, J., Tai, S. S., Killaspy, H., Osborn, D., Popelyuk, D., & Nazareth, I. (2008). A Systematic Review of Mental Disorder, Suicide, and Deliberate Self Harm in Lesbian, Gay and Bisexual People. BMC Psychiatry, 8(1), 70‒87.Google Scholar

Krueger, R. F., Caspi, A., Moffitt, T. E., & Silva, P. A. (1998). The Structure and Stability of Common Mental Disorders (DSM-III-R): A Longitudinal-Epidemiological Study. Journal of Abnormal Psychology, 107, 216–227.Google Scholar

Ladouceur, C. D., Peper, J. S., Crone, E. A., & Dahl, R. E. (2012). White Matter Development in Adolescence: The Influence of Puberty and Implications for Affective Disorders. Developmental Cognitive Neuroscience, 2, 36‒54.Google Scholar

Lanza, S. T., & Collins, L. M. (2002). Pubertal Timing and the Onset of Substance Use in Females during Early Adolescence. Prevention Science, 3(1), 69‒82.Google Scholar

Lee, P. A., Guo, S. S., & Kulin, H. E. (2001). Age of Puberty: Data from the United States of America. APMIS Journal of Pathology, Microbiology, and Immunology, 109(S103), 81‒88.Google Scholar

Lee, Y., & Styne, D. (2013). Influences on the Onset and Tempo of Puberty in Human Beings and Implications for Adolescent Psychological Development. Hormones and Behavior, 64(2), 250‒261.Google Scholar

Lerner, R. M. (2006). Developmental Science, Developmental Systems, and Contemporary Theories. In Lerner, R. M. (Ed.), Handbook of Child Psychology: Vol. 1. Theoretical Models of Human Development (pp. 1–17). Hoboken, NJ: Wiley.Google Scholar

Lewinsohn, P. M., Zinbarg, R., Seeley, J. R., Lewinsohn, M., & Sack, W. H. (1997). Lifetime Comorbidity among Anxiety Disorders and between Anxiety Disorders and Other Mental Disorders in Adolescents. Journal of Anxiety Disorders, 11(4), 377‒394.Google Scholar

Lewinsohn, P. M., Shankman, S. A., Gau, J. M., & Klein, D. N. (2004). The Prevalence and Co-Morbidity of Subthreshold Psychiatric Conditions. Psychological Medicine, 34(4), 613–622.Google Scholar

Lynne, S. D., Graber, J. A., Nichols, T. R., Brooks-Gunn, J., & Botvin, G. J. (2007). Links between Pubertal Timing, Peer Influences, and Externalizing Behaviors among Urban Students followed through Middle School. Journal of Adolescent Health, 40(2), 181.e7–181.e13.Google Scholar

Lynne-Landsman, S. D. & Wagenaar, A. C. (2015). Alcohol Policy: Interventions to Prevent Youth Alcohol Use. In Scheier, L. M. (Ed.), Handbook of Adolescent Drug Use Prevention: Research, Intervention Strategies, and Practice (pp. 329–341). Washington, DC: American Psychological Association.Google Scholar

Lynne-Landsman, S. D., Graber, J. A., & Andrews, J. A. (2010). Do Trajectories of Household Risk in Childhood Moderate Pubertal Timing Effects on Substance Initiation in Middle School? Developmental Psychology, 46(4), 853‒868.Google Scholar

Lynne-Landsman, S. D., Livingston, M. D., & Wagenaar, A. C. (2013). Effects of State Medical Marijuana Laws on Adolescent Marijuana Use. American Journal of Public Health, 103(8), 1500–1506.Google Scholar

Martí-Henneberg, C., & Vizmanos, B. (1997). The Duration of Puberty in Girls Is Related to the Timing of Its Onset. Journal of Pediatrics, 131(4), 618‒621.Google Scholar

Mendle, J. (2014). Beyond Pubertal Timing: New Directions for Studying Individual Differences in Development. Current Directions in Psychological Science, 23(3), 215‒219.Google Scholar

Mendle, J., & Ferrero, J. (2012). Detrimental Psychological Outcomes Associated with Pubertal Timing in Adolescent Boys. Developmental Review, 32(1), 49‒66.Google Scholar

Mussen, P. H., & Jones, M. C. (1957). Self-Conceptions, Motivations, and Interpersonal Attitudes of Late- and Early-Maturing Boys. Child Development, 28(2), 243‒256.Google Scholar

Meyer, I. H. (2003). Prejudice, Social Stress, and Mental Health in Lesbian, Gay, and Bisexual Populations: Conceptual Issues and Research Evidence. Psychological Bulletin, 129(5), 674‒697.Google Scholar

Natsuaki, M. N., Leve, L. D., & Mendle, J. (2011). Going Through the Rites of Passage: Timing and Transition of Menarche, Childhood Sexual Abuse, and Anxiety Symptoms in Girls. Journal of Youth and Adolescence, 40(10), 1357‒1370.Google Scholar

Negriff, S., & Susman, E. J. (2011). Pubertal Timing, Depression, and Externalizing Problems: A Framework, Review, and Examination of Gender Differences. Journal of Research on Adolescence, 21(3), 717‒746.Google Scholar

Parent, A. S., Teilmann, G., Juul, A., Skakkebaek, N. E., Toppari, J., & Bourguignon, J. P. (2003). The Timing of Normal Puberty and the Age Limits of Sexual Precocity: Variations around the World, Secular Trends, and Changes after Migration. Endocrine Reviews, 24(5), 668‒693.Google Scholar

Peper, J. S., & Dahl, R. E. (2013). The Teenage Brain: Surging Hormones – Brain-Behavior Interactions during Puberty. Current Directions in Psychological Science, 22(2), 134‒139.Google Scholar

Peper, J. S., Pol, H. E. H., Crone, E. A., & Van Honk, J. (2011). Sex Steroids and Brain Structure in Pubertal Boys and Girls: A Mini-Review of Neuroimaging Studies. Neuroscience, 191, 28–37.Google Scholar

Petersen, A. C., Crockett, L., Richards, M., & Boxer, A. (1988). A Self-Report Measure of Pubertal Status: Reliability, Validity, and Initial Norms. Journal of Youth and Adolescence, 17(2), 117‒133.Google Scholar

Pfeifer, J. H., & Allen, N. B. (2012). Arrested Development? Reconsidering Dual-Systems Models of Brain Function in Adolescence and Disorders. Trends in Cognitive Sciences, 16(6), 322–329.Google Scholar

Pomerantz, H., Parent, J., Forehand, R., Breslend, N. L., & Winer, J. P. (2017). Pubertal Timing and Youth Internalizing Psychopathology: The Role of Relational Aggression. Journal of Child and Family Studies, 26(2), 416‒423.Google Scholar

Poteat, V. P., Sinclair, K. O., DiGiovanni, C. D., Koenig, B. W., & Russell, S. T. (2012). Gay-Straight Alliances Are Associated with Student Health: A Multischool Comparison of LGBTQ and Heterosexual Youth. Journal of Research on Adolescence, 23(2), 319‒330.Google Scholar

Raifman, J., Moscoe, E., Austin, S. B., & McConnell, M. (2017). Difference-in-Differences Analysis of the Association between State Same-Sex Marriage Policies and Adolescent Suicide Attempts. JAMA Pediatrics, 171(4), 350–356.Google Scholar

Rosario, M., Schrimshaw, E. W., Hunter, J., & Gwadz, M. (2002). Gay-Related Stress and Emotional Distress among Gay, Lesbian and Bisexual Youths: A Longitudinal Examination. Journal of Consulting and Clinical Psychology, 70(4), 967‒975.Google Scholar

Rusby, J. C., Westling, E., Crowley, R., & Light, J. M. (2018). Legalization of Recreational Marijuana and Community Sales Policy in Oregon: Impact on Adolescent Willingness and Intent to Use, Parent Use, and Adolescent Use. Psychology of Addictive Behaviors, 32(1), 84–92.Google Scholar

Sannino, S., Chini, B., & Grinevich, V. (2016). Lifespan Oxytocin Signaling: Maturation, Flexibility, and Stability in Newborn, Adolescent, and Aged Brain. Developmental Neurobiology, 77, 158‒168.Google Scholar

Schulz, K. M., Molenda-Figueira, H. A., & Sisk, C. L. (2009). Back to the Future: The Organizational-Activational Hypothesis Adapted to Puberty and Adolescence. Hormones and Behavior, 55(5), 597‒604.Google Scholar

Shirtcliff, E. A., Dahl, R. E., & Pollak, S. D. (2009). Pubertal Development: Correspondence between Hormonal and Physical Development. Child Development, 80(2), 327‒337.Google Scholar

Shulman, E. P., Smith, A. R., Silva, K., Icenogle, G., Duell, N., Chein, J., & Steinberg, L. (2016). The Dual Systems Model: Review, Reappraisal, and Reaffirmation. Developmental Cognitive Neuroscience, 17, 103–117.Google Scholar

Sisk, C. L., & Zehr, J. L. (2005). Pubertal Hormones Organize the Adolescent Brain and Behavior. Frontiers in Neuroendocrinology, 26(3–4), 163‒174.Google Scholar

Steinberg, L. (2010). Commentary: A Behavioral Scientist Looks at the Science of Adolescent Brain Development. Brain and Cognition, 72(1), 160‒164.Google Scholar

Steinberg, L., & Morris, A. S. (2001). Adolescent Development. Annual Review of Psychology, 52(1), 83‒110.Google Scholar

Styne, D. M. & Grumbach, M. M. (2011). Puberty, Ontogeny, Neuroendocrinology, Physiology, and Disorders. In Melmed, S, Polonsky, K. S., Larsen, P. R., & Kronenberg, H. M (Eds.), Williams Textbook of Endocrinology (12th edn., pp. 1054‒1201). Philadelphia, PA: Saunders, Elsevier.Google Scholar

Suleiman, A. B., & Dahl, R. E. (2017). Leveraging Neuroscience to Inform Adolescent Health: The Need for an Innovative Transdisciplinary Developmental Science of Adolescence. Journal of Adolescent Health, 60(3), 240‒248.Google Scholar

Sun, S. S., Schubert, C. M., Chumlea, W. C., Roche, A. F., Kulin, H. E., Lee, P. A., … Ryan, A. S. (2002). National Estimates of the Timing of Sexual Maturation and Racial Differences among US Children. Pediatrics, 110(5), 911‒919.Google Scholar

Susman, E. J., & Dorn, L. D. (2009). Puberty: Its Role in Development. In Lerner, R. M. & Steinberg, L. (Eds.), Handbook of Adolescent Psychology: Individual Bases of Adolescent Development (pp. 116‒151). Hoboken, NJ: Wiley.Google Scholar

Susman, E. J., Houts, R. M., Steinberg, L., Belsky, J., Cauffman, E., DeHart, G., … Halpern-Felsher, B. L. (2010). Longitudinal Development of Secondary Sexual Characteristics in Girls and Boys between Ages 9½ and 15½ Years. Archives of Pediatrics & Adolescent Medicine, 164(2), 166‒173.Google Scholar

Tanner, J. M., & Whitehouse, R. H. (1976). Clinical Longitudinal Standards for Height, Weight, Height Velocity, Weight Velocity, and Stages of Puberty. Archives of Disease in Childhood, 51(3), 170‒179.Google Scholar

Tebbe, E. A., & Moradi, B. (2016). Suicide Risk in Trans Populations: An Application of Minority Stress Theory. Journal of Counseling Psychology, 63(5), 520‒533.Google Scholar

Teilmann, G., Pedersen, C. B., Jensen, T. K., Skakkebæk, N. E., & Juul, A. (2005). Prevalence and Incidence of Precocious Pubertal Development in Denmark: An Epidemiologic Study Based on National Registries. Pediatrics, 116(6), 1323‒1328.Google Scholar

Ullsperger, J. M., & Nikolas, M. A. (2017). A Meta-Analytic Review of the Association between Pubertal Timing and Psychopathology in Adolescence: Are There Sex Differences in Risk?. Psychological Bulletin, 143(9), 903‒938.Google Scholar

Wall, M. M., Mauro, C., Hasin, D. S., Keyes, K. M., Cerdá, M., Martins, S. S., & Feng, T. (2016). Prevalence of Marijuana Use Does not Differentially Increase among Youth after States Pass Medical Marijuana Laws: Commentary on Stolzenberg et al. (2015) and Reanalysis of US National Survey on Drug Use in Households Data 2001–2011. International Journal of Drug Policy, 29, 9–13.Google Scholar

Walvoord, E. C. (2010). The Timing of Puberty: Is It Changing? Does It Matter?. Journal of Adolescent Health, 47(5), 433‒439.Google Scholar

Wen, H., Hockenberry, J. M., & Cummings, J. R. (2015). The Effect of Medical Marijuana Laws on Adolescent and Adult Use of Marijuana, Alcohol, and Other Substances. Journal of Health Economics, 42, 64–80.Google Scholar

Williams, D. R., & Mohammed, S. A. (2009). Discrimination and Racial Disparities in Health: Evidence and Needed Research. Journal of Behavioral Medicine, 32(1), 20‒47.Google Scholar

Williams, D. R., Costa, M. V., Odunlami, A. O., & Mohammed, S. A. (2008). Moving Upstream: How Interventions That Address the Social Determinants of Health Can Improve Health and Reduce Disparities. Journal of Public Health Management and Practice, 14(Supplement), S8‒S17.Google Scholar

References

Bailey, A., Phillips, W., & Rutter, M. (1996). Autism: Towards an Integration of Clinical, Genetic, Neuropsychological, and Neurobiological Perspectives. Journal of Child Psychology and Psychiatry and Allied Disciplines, 37(1), 89–126.Google Scholar

Bergen, S. E., Gardner, C. O., & Kendler, K. S. (2007). Age-Related Changes in Heritability of Behavioral Phenotypes over Adolescence and Young Adulthood: A Meta-Analysis. Twin Research and Human Genetics, 10(3), 423–433.Google Scholar

Biederman, J., Faraone, S. V., Keenan, K., Benjamin, J., Krifcher, B., Moore, C., … Steingard, R. (1992). Further Evidence for Family-Genetic Risk Factors in Attention Deficit Hyperactivity Disorder: Patterns of Comorbidity in Probands and Relatives in Psychiatrically and Pediatrically Referred Samples. Archives of General Psychiatry, 49(9), 728–738.Google Scholar

Boomsma, D. D., Van Beijsterveldt, C. E. M., Bartels, M., & Hudziak, J. J. (2008). Genetic and Environmental Influences on Anxious/Depression: A Longitudinal Study in 3- to 12-Year-Old Children. In Hudziak, J. J. (Ed.), Developmental Psychopathology and Wellness: Genetic and Environmental Influences. Arlington, VA: American Psychiatric Publishing.Google Scholar

Burt, S. A. (2009). Rethinking Environmental Contributions to Child and Adolescent Psychopathology: A Meta-Analysis of Shared Environmental Influences. Psychological Bulletin, 135(4), 608–637.Google Scholar

Burt, S. A., McGue, M., Krueger, R. F., & Iacono, W. G. (2005). Sources of Covariation among the Child-Externalizing Disorders: Informant Effects and the Shared Environment. Psychological Medicine, 35(8), 1133–1144.Google Scholar

Caspi, A., Houts, R. M., Belsky, D. W., Goldman-Mellor, S. J., Harrington, H., Israel, S., … Moffitt, T. E. (2014). The p Factor: One General Psychopathology Factor in the Structure of Psychiatric Disorders? Clinical Psychological Science, 2(2), 119–137.Google Scholar

Chang, Z., Lichtenstein, P., Asherson, P. J., & Larsson, H. (2013). Developmental Twin Study of Attention Problems: High Heritabilities throughout Development. JAMA Psychiatry, 70(3), 311–318.Google Scholar

Chen, Q., Brikell, I., Lichtenstein, P., Serlachius, E., Kuja-Halkola, R., Sandin, S., & Larsson, H. (2017). Familial Aggregation of Attention-Deficit/Hyperactivity Disorder. Journal of Child Psychology and Psychiatry and Allied Disciplines, 58(3), 231–239.Google Scholar

Colvert, E., Tick, B., & McEwen, F. (2015). Heritability of Autism Spectrum Disorder in a UK Population-Based Twin Sample. JAMA Psychiatry, 72(5), 415–423.Google Scholar

Cosgrove, V. E., Rhee, S. H., Gelhorn, H. L., Boeldt, D., Corley, R. C., Ehringer, M. A., … Hewitt, J. K. (2011). Structure and Etiology of Co-occurring Internalizing and Externalizing Disorders in Adolescents. Journal of Abnormal Child Psychology, 39, 109–123.CrossRef Google Scholar PubMed

D’Onofrio, B. M., Lahey, B. B., Turkheimer, E., & Lichtenstein, P. (2013). Critical Need for Family-Based, Quasi-Experimental Designs in Integrating Genetic and Social Science Research. American Journal of Public Health, 103(S1), S46–S55.Google Scholar

DeFries, J. C., & Fulker, D. W. (1988). Multiple Regression Analysis of Twin Data: Etiology of Deviant Scores versus Individual Differences. Acta Geneticae Medicae et Gemellologiae, 37(3–4), 205–216.Google Scholar

Eley, T. C., Deater-Deckard, K., Fombonne, E., Fulker, D. W., & Plomin, R. (1998). An Adoption Study of Depressive Symptoms in Middle Childhood. The Journal of Child Psychology and Psychiatry and Allied Disciplines, 39(3), 337–345.Google Scholar

Falconer, D. S. (1965). The Inheritance of Liability to Certain Diseases, Estimated from the Incidence among Relatives. Annals of Human Genetics, 29(1), 51–76.Google Scholar

Faraone, S., Biederman, J., & Monuteaux, M. (2000). Toward Guidelines for Pedigree Selection in Genetic Studies of Attention Deficit Hyperactivity Disorder. Genetic Epidemiology, 18(1), 1–16.Google Scholar

Faraone, S. V., & Larsson, H. (2018). Genetics of Attention Deficit Hyperactivity Disorder. Molecular Psychiatry, 24(4), 562–575.Google Scholar

Franić, S., Middeldorp, C. M., Dolan, C. V., Ligthart, L., & Boomsma, D. I. (2010). Childhood and Adolescent Anxiety and Depression: Beyond Heritability. Journal of the American Academy of Child and Adolescent Psychiatry, 49(8), 820–829.Google Scholar

Ge, X., Conger, R. D., Cadoret, R. J., Neiderhiser, J. M., Yates, W., Troughton, E., & Stewart, M. A. (1996). The Developmental Interface between Nature and Nurture: A Mutual Influence Model of Child Antisocial Behavior and Parent Behaviors. Developmental Psychology, 32(4), 574–589.Google Scholar

Ghirardi, L., Brikell, I., Kuja-Halkola, R., Freitag, C. M., Franke, B., Asherson, P., … Larsson, H. (2017). The Familial Co-Aggregation of ASD and ADHD: A Register-Based Cohort Study. Molecular Psychiatry, 23(2), 257–262.Google Scholar

Gregory, A. M., & Eley, T. C. (2007). Genetic Influences on Anxiety in Children: What We’ve Learned and Where We’re Heading. Clinical Child and Family Psychology Review, 10(3), 199–212.Google Scholar

Harold, G. T., Leve, L. D., Barrett, D., Elam, K., Neiderhiser, J. M., Natsuaki, M. N., … Thapar, A. (2013). Biological and Rearing Mother Influences on Child ADHD Symptoms: Revisiting the Developmental Interface between Nature and Nurture. Journal of Child Psychology and Psychiatry and Allied Disciplines, 54(10), 1038–1046.Google Scholar

Holmboe, K., Rijsdijk, F. V., Hallett, V., Happe, F., Plomin, R., & Ronald, A. (2014). Strong Genetic Influences on the Stability of Autistic Traits in Childhood. Journal of the American Academy of Child and Adolescent Psychiatry, 53(2), 221–230.Google Scholar

Kan, K. J., van Beijsterveldt, C. E., Bartels, M., & Boomsma, D. I. (2014). Assessing Genetic Influences on Behavior: Informant and Context Dependency as Illustrated by the Analysis of Attention Problems. Behavior Genetics, 44(4), 326–336.Google Scholar

Kendler, K. S., & Baker, J. H. (2007). Genetic Influences on Measures of the Environment: A Systematic Review. Psychological Medicine, 37(5), 615–626.Google Scholar

Kuntsi, J., Rijsdijk, F., Ronald, A., Asherson, P., & Plomin, R. (2005). Genetic Influences on the Stability of Attention-Deficit/Hyperactivity Disorder Symptoms from Early to Middle Childhood. Biological Psychiatry, 57(6), 647–654.Google Scholar

Lahey, B. B., Van Hulle, C. A., Singh, A. L., Waldman, I. D., & Rathouz, P. J. (2011). Higher-Order Genetic and Environmental Structure of Prevalent Forms of Child and Adolescent Psychopathology. Archives of General Psychiatry, 68(2), 181–189.Google Scholar

Lahey, B. B., Krueger, R. F., Rathouz, P. J., Waldman, I. D., & Zald, D. H. (2017). A Hierarchical Causal Taxonomy of Psychopathology across the Life Span. Psychological Bulletin, 143(2), 142–186.Google Scholar

Larsson, H., Lichtenstein, P., & Larsson, J. O. (2006). Genetic Contributions to the Development of ADHD Subtypes from Childhood to Adolescence. Journal of the American Academy of Child and Adolescent Psychiatry, 45(8), 973–981.Google Scholar

Larsson, H., Viding, E., Rijsdijk, F. V., & Plomin, R. (2008). Relationships between Parental Negativity and Childhood Antisocial Behavior Over Time: A Bidirectional Effects Model in a Longitudinal Genetically Informative Design. Journal of Abnormal Child Psychology, 36(5), 633–645.Google Scholar

Larsson, H., Anckarsater, H., Rastam, M., Chang, Z., & Lichtenstein, P. (2012). Childhood Attention-Deficit Hyperactivity Disorder as an Extreme of a Continuous Trait: A Quantitative Genetic Study of 8,500 Twin Pairs. Journal of Child Psychology and Psychiatry and Allied Disciplines, 53(1), 73–80.Google Scholar

Levy, F., Hay, D., McStephen, M., Wood, C., & Waldman, I. (1997). Attention-Deficit Hyperactivity Disorder: A Category or a Continuum? Genetic Analysis of a Large-Scale Twin Study. Journal of the American Academy of Child and Adolescent Psychiatry, 36(6), 737–744.Google Scholar

Lichtenstein, P., Carlström, E., Råstam, M., Gillberg, C., & Anckarsäter, H. (2010). The Genetics of Autism Spectrum Disorders and Related Neuropsychiatric Disorders in Childhood. American Journal of Psychiatry, 167(11), 1357–1363.Google Scholar

Lifford, K. J., Harold, G. T., & Thapar, A. (2009). Parent-Child Hostility and Child ADHD Symptoms: A Genetically Sensitive and Longitudinal Analysis. Journal of Child Psychology and Psychiatry and Allied Disciplines, 50(12), 1468–1476.Google Scholar

Lundström, S., Chang, Z., Kerekes, N., Gumpert, C. H., Råstam, M., & Gillberg, C. (2011). Autistic-Like Traits and Their Association with Mental Health Problems in Two Nationwide Twin Cohorts of Children and Adults. Psychological Medicine, 41(11), 2423–2433.Google Scholar

Martin, J., Taylor, M. J., & Lichtenstein, P. (2017). Assessing the Evidence for Shared Genetic Risks across Psychiatric Disorders and Traits. Psychological Medicine, 48(11), 1–16.Google Scholar

McGue, M., Osler, M., & Christensen, K. (2010). Causal Inference and Observational Research: The Utility of Twins. Perspectives on Psychological Science, 5(5), 546–556.Google Scholar

McGuffin, P., Owen, M. J., & Gottesman, I. I. (2004). Psychiatric Genetics and Genomics: Oxford: Oxford University Press.Google Scholar

Moberg, T., Lichtenstein, P., Forsman, M., & Larsson, H. (2011). Internalizing Behavior in Adolescent Girls Affects Parental Emotional Overinvolvement: A Cross-Lagged Twin Study. Behavior Genetics, 41(2), 223–233.Google Scholar

Neale, M., & Cardon, L. (1992). Methodology for Genetic Studies of Twins and Families. Dordrecht: Kluwer Academic.Google Scholar

Nikolas, M. A., & Burt, S. A. (2010). Genetic and Environmental Influences on ADHD Symptom Dimensions of Inattention and Hyperactivity: A Meta-Analysis. Journal of Abnormal Psychology, 119(1), 1–17.Google Scholar

Nivard, M. G., Dolan, C. V., Kendler, K. S., Kan, K. J., Willemsen, G., van Beijsterveldt, C. E. M., … Boomsma, D. I. (2014). Stability in Symptoms of Anxiety and Depression as a Function of Genotype and Environment: A Longitudinal Twin Study from Ages 3 to 63 Years. Psychological Medicine, 45(5), 1039–1049.Google Scholar

Pettersson, E., Anckarsater, H., Gillberg, C., & Lichtenstein, P. (2013). Different Neurodevelopmental Symptoms Have a Common Genetic Etiology. Journal of Child Psychology and Psychiatry and Allied Disciplines, 54(12), 1356–1365.Google Scholar

Pike, A., McGuire, S., Hetherington, E. M., Reiss, D., & Plomin, R. (1996). Family Environment and Adolescent Depressive Symptoms and Antisocial Behavior: A Multivariate Genetic Analysis. Developmental Psychology, 32(4), 590–603.Google Scholar

Pingault, J., Viding, E., Galéra, C., Greven, C. U., Zheng, Y., Plomin, R., & Rijsdijk, F. (2015). Genetic and Environmental Influences on the Developmental Course of Attention-Deficit/Hyperactivity Disorder Symptoms from Childhood to Adolescence. JAMA Psychiatry, 72(7), 651–658.Google Scholar

Plomin, R., & Bergeman, C. S. (2011). The Nature of Nurture: Genetic Influence on “Environmental” Measures. Behavioral and Brain Sciences, 14(3), 373–386.Google Scholar

Plomin, R., Loehlin, J. C., & DeFries, J. (1985). Genetic and Environmental Components of “Environmental” Influences. Developmental Psychology, 21(3), 391–402.Google Scholar

Plomin, R., DeFries, J. C., Knopik, V. S., & Neiderhiser, J. (2013). Behavioral Genetics. New York: Worth Publishers.Google Scholar

Plomin, R., DeFries, J. C., Knopik, V. S., & Neiderhiser, J. M. (2016). Top 10 Replicated Findings from Behavioral Genetics. Perspectives on Psychological Science: A Journal of the Association for Psychological Science, 11(1), 3–23.Google Scholar

Polderman, T. J., Benyamin, B., de Leeuw, C. A., Sullivan, P. F., van Bochoven, A., Visscher, P. M., & Posthuma, D. (2015). Meta-Analysis of the Heritability of Human Traits Based on Fifty Years of Twin Studies. Nature Genetics, 47(7), 702–709.Google Scholar

Posthuma, D., & Polderman, T. J. (2013). What Have We Learned from Recent Twin Studies about the Etiology of Neurodevelopmental Disorders? Current Opinion in Neurology, 26(2), 111–121.Google Scholar

Posthuma, D., Beem, A. L., de Geus, E. J., van Baal, G. C., von Hjelmborg, J. B., Iachine, I., & Boomsma, D. I. (2003). Theory and Practice in Quantitative Genetics. Twin Research, 6(5), 361–376.Google Scholar

Rhee, S. H., & Waldman, I. D. (2002). Genetic and Environmental Influences on Antisocial Behavior: A Meta-Analysis of Twin and Adoption Studies. Psychological Bulletin, 128(3), 490–529.Google Scholar

Rice, F., Harold, G., & Thapar, A. (2002). The Genetic Aetiology of Childhood Depression: A Review. Journal of Child Psychology and Psychiatry, 43(1), 65–79.Google Scholar

Rietveld, M. J., Hudziak, J. J., Bartels, M., van Beijsterveldt, C. E., & Boomsma, D. I. (2004). Heritability of Attention Problems in Children: Longitudinal Results from a Study of Twins, Age 3 to 12. Journal of Child Psychology and Psychiatry and Allied Disciplines, 45(3), 577–588.Google Scholar

Rijsdijk, F. V., & Sham, P. C. (2002). Analytic Approaches to Twin Data Using Structural Equation Models. Briefings in Bioinformatics, 3(2), 119–133.Google Scholar

Ronald, A., Simonoff, E., Kuntsi, J., Asherson, P., & Plomin, R. (2008). Evidence for Overlapping Genetic Influences on Autistic and ADHD Behaviours in a Community Twin Sample. Journal of Child Psychology and Psychiatry, and Allied Disciplines, 49(5), 535–542.Google Scholar

Sandin, S., Lichtenstein, P., Kuja-Halkola, R., Hultman, C., Larsson, H., & Reichenberg, A. (2017). The Heritability of Autism Spectrum Disorder. JAMA, 318(12), 1182–1184. doi:10.1001/jama.2017.12141 Google Scholar

Smalley, S. L., Asarnow, R. F., & Spence, M. A. (1988). Autism and Genetics: A Decade of Research. Archives of General Psychiatry, 45(10), 953–961.Google Scholar

Taylor, M. J., Gillberg, C., Lichtenstein, P., & Lundström, S. (2017). Etiological Influences on the Stability of Autistic Traits from Childhood to Early Adulthood: Evidence from a Twin Study. Molecular Autism, 8(1), 5.Google Scholar

Thapar, A., & Stergiakouli, E. (2008). Genetic Influences on the Development of Childhood Psychiatric Disorders. Psychiatry, 7(7), 277–281.Google Scholar

Tick, B., Bolton, P., Happe, F., Rutter, M., & Rijsdijk, F. (2016). Heritability of Autism Spectrum Disorders: A Meta-Analysis of Twin Studies. Journal of Child Psychology and Psychiatry and Allied Disciplines, 57(5), 585–595.Google Scholar

Trzaskowski, M., Zavos, H. M. S., Haworth, C. M. A., Plomin, R., & Eley, T. C. (2012). Stable Genetic Influence on Anxiety-Related Behaviours Across Middle Childhood. Journal of Abnormal Child Psychology, 40(1), 85–94.Google Scholar

Van den Oord, E. J., Boomsma, D. I., & Verhulst, F. C. (1994). A Study of Problem Behaviors in 10- to 15-Year-Old Biologically Related and Unrelated International Adoptees. Behavior Genetics, 24(3), 193–205.Google Scholar

References

Ahadi, S., & Diener, E. (1989). Multiple Determinants and Effect Size. Journal of Personality and Social Psychology, 56(3), 398‒406.Google Scholar

Anderson, E. R. (1993). Analyzing Change in Short-Term Longitudinal Research Using Cohort-Sequential Designs. Journal of Consulting and Clinical Psychology, 61(6), 929‒940.Google Scholar

Barry, A. E. (2005). How Attrition Impacts the Internal and External Validity of Longitudinal Research. Journal of School Health, 75, 267‒270.Google Scholar

Benjamin, D. J., Berger, J. O., Johannesson, M., Nosek, B. A., Wagenmakers, E. J., Berk, R., … & Cesarini, D. (2018). Redefine Statistical Significance. Nature Human Behaviour, 2(1), 6‒10.Google Scholar

Block, J. (1993). Studying Personality the Long Way. In Funder, D. C., Parke, R. D., Tomlinson Keasy, C., & Widaman, K. F. (Eds.). Studying Lives through Time: Personality and Development (pp. 9–41). Washington, DC: American Psychological Association.Google Scholar

Booker, C. L., Harding, S., & Benzeval, M. (2011). A Systematic Review of the Effect of Retention Methods in Population-Based Cohort Studies. BMC Public Health, 11(1), 249.Google Scholar

Bosco, F. A., Aguinis, H., Singh, K., Field, J. G., & Pierce, C. A. (2015). Correlational Effect Size Benchmarks. Journal of Applied Psychology, 100(2), 431‒449.Google Scholar

Button, K. S., Ioannidis, J. P., Mokrysz, C., Nosek, B. A., Flint, J., Robinson, E. S., & Munafò, M. R. (2013). Power Failure: Why Small Sample Size Undermines the Reliability of Neuroscience. Nature Reviews Neuroscience, 14(5), 365‒376.Google Scholar

Campbell, L., Loving, T. J., & Lebel, E. P. (2014). Enhancing Transparency of the Research Process to Increase Accuracy of Findings: A Guide for Relationship Researchers. Personal Relationships, 21(4), 531‒545.Google Scholar

Capaldi, D., & Patterson, G. R. (1987). An Approach to the Problem of Recruitment and Retention Rates for Longitudinal Research. Behavioral Assessment, 9, 169‒178.Google Scholar

Caspi, A. (1998). Personality Development across the Life Course. In Damon, W. (Ed.). Handbook of Child Psychology, Vol. 3: Social, Emotional, and Personality Development (5th edn.) (pp. 311‒388). New York: Wiley.Google Scholar

Cattell, R. B. (1970). Separating Endogenous, Exogenous, Epogenic, and Epogenic Component Curves in Developmental Data. Developmental Psychology, 3, 151‒162.Google Scholar

Claus, R. E., Kindleberger, L. R., & Dugan, M. C. (2002). Predictors of Attrition in a Longitudinal Study of Substance Abusers. Journal of Psychoactive Drugs, 34(1), 69‒74.Google Scholar

Cohen, J. (1988). Statistical Power Analysis for the Behavioral Sciences (2nd edn.). Hillsdale, NJ: Erlbaum.Google Scholar

Cole, D. A., & Maxwell, S. E. (2003). Testing Mediational Models with Longitudinal Data: Questions and Tips in the Use of Structural Equation Modeling. Journal of Abnormal Psychology, 112, 538‒577.Google Scholar

Collins, L. M. (2006). Analysis of Longitudinal Data: The Integration of Theoretical Model, Temporal Design, and Statistical Model. Annual Review of Psychology, 57, 505–528.Google Scholar

Conger, R. D., Lorenz, F. O., & Wickrama, K. A. S. (2004). Studying Change in Family Relationships: The Findings and Their Implications. In Conger, R. D., Lorenz, F. O., & Wickrama, K. A. S. (Eds.). Continuity and Change in Family Relations: Theory, Methods, and Empirical Findings (pp. 383‒403). Mahwah, NJ: Lawrence Erlbaum.Google Scholar

Connelly, B. S., & Ones, D. S. (2010). An Other Perspective on Personality: Meta-Analytic Integration of Observers’ Accuracy and Predictive Validity. Psychological Bulletin, 136(6), 1092‒1122.Google Scholar

Cotter, R. B., Burke, J. D., Loeber, R., & Navratil, J. L. (2002). Innovative Retention Methods in Longitudinal Research: A Case Study of the Developmental Trends Study. Journal of Child and Family Studies, 11, 485‒498.Google Scholar

Davis, L. L., Broome, M. E., & Cox, R. P. (2002). Maximizing Retention in Community‐Based Clinical Trials. Journal of Nursing Scholarship, 34(1), 47‒53.Google Scholar

Donnellan, M. B., & Conger, R. D. (2007). Designing and Implementing Longitudinal Studies. In Robins, R. W, Chris Fraley, R., & Krueger, R. F (Eds.). Handbook of Research Methods in Personality Psychology (pp. 21‒36.). New York: Guilford Press.Google Scholar

Donnellan, M. B., Roisman, G. L., Fraley, R. C., & Lucas, R. E. (2013, Summer). Methodological Reform 101 for Developmental Researchers. Developmental Psychologist Division 7 Newsletter, 34–40.Google Scholar

Dormann, C., & Griffin, M. A. (2015). Optimal Time Lags in Panel Studies. Psychological Methods, 20, 489‒505.Google Scholar

Faden, V. B., Day, N. L., Windle, M., Windle, R., Grube, J. W., Molina, B. S., … & Sher, K. J. (2004). Collecting Longitudinal Data through Childhood, Adolescence, and Young Adulthood: Methodological Challenges. Alcoholism: Clinical and Experimental Research, 28, 330‒340.Google Scholar

Ferrer, E., & McArdle, J. J. (2003). Alternative Structural Equation Models for Multivariate Longitudinal Data Analysis. Structural Equation Modeling, 10, 493‒524.Google Scholar

Fine, M. A., & Kurdek, L. A. (1999). Reflections on Determining Authorship Credit and Authorship Order on Faculty-Student Collaborations. American Psychologist, 48, 1141–1147.Google Scholar

Fraley, R. C., & Roberts, B. W. (2005). Patterns of Continuity: A Dynamic Model for Conceptualizing the Stability of Individual Differences in Psychological Constructs across the Life Course. Psychological Review, 112(1), 60‒74.Google Scholar

Fraley, R. C., & Vazire, S. (2014). The N-Pact Factor: Evaluating the Quality of Empirical Journals with Respect to Sample Size and Statistical Power. PloS One, 9(10), e109019.Google Scholar

Fumagalli, L., Laurie, H., & Lynn, P. (2013). Experiments with Methods to Reduce Attrition in Longitudinal Surveys. Journal of the Royal Statistical Society: Series A (Statistics in Society), 176(2), 499‒519.Google Scholar

Gignac, G. E., & Szodorai, E. T. (2016). Effect Size Guidelines for Individual Differences Researchers. Personality and Individual Differences, 102, 74‒78.Google Scholar

Gollob, H. F., & Reichardt, C. S. (1987). Taking Account of Time Lags in Causal Models. Child Development, 58, 80‒92.Google Scholar

Graziotti, A. L., Hammond, J., Messinger, D. S., Bann, C. M., Miller‐Loncar, C., Twomey, J. E., … & Alexander, B. (2012). Maintaining Participation and Momentum in Longitudinal Research Involving High‐Risk Families. Journal of Nursing Scholarship, 44(2), 120‒126.Google Scholar

Grimm, K. J., Davoudzadeh, P., & Ram, N. (2017). IV. Developments in the Analysis of Longitudinal Data. Monographs of the Society for Research in Child Development, 82(2), 46‒66.Google Scholar

Gustavson, K., von Soest, T., Karevold, E., & Røysamb, E. (2012). Attrition and Generalizability in Longitudinal Studies: Findings from a 15-Year Population-Based Study and a Monte Carlo Simulation Study. BMC Public Health, 12(1), 918.Google Scholar

Hartmann, D. P. (2005). Assessing Growth in Longitudinal Investigations: Selected Measurement and Design Issues. In Teti, D. M. (Ed.), Handbook of Research Methods in Developmental Science (pp. 319‒339). Malden, MA: Blackwell.Google Scholar

Hemphill, J. F. (2003). Interpreting the Magnitudes of Correlation Coefficients. American Psychologist, 58, 78‒79.Google Scholar

Henrich, J., Heine, S. J., & Norenzayan, A. (2010). The Weirdest People in the World? Behavioral and Brain Sciences, 33, 62‒135.Google Scholar

Hill, C. J., Bloom, H. S., Black, A. R., & Lipsey, M. W. (2008). Empirical Benchmarks for Interpreting Effect Sizes in Research. Child Development Perspectives, 2(3), 172‒177.Google Scholar

Humbad, M. N., Donnellan, M. B., Klump, K. L., & Burt, S. A. (2011). Development of the Brief Romantic Relationship Interaction Coding Scheme (BRRICS). Journal of Family Psychology, 25(5), 759‒769.Google Scholar

John, L. K., Loewenstein, G., & Prelec, D. (2012). Measuring the Prevalence of Questionable Research Practices with Incentives for Truth Telling. Psychological Science, 23(5), 524‒532.Google Scholar

Kashy, D. A., Donnellan, M. B., Ackerman, R. A., & Russell, D. W. (2009). Reporting and Interpreting Research in PSPB: Practices, Principles, and Pragmatics. Personality and Social Psychology Bulletin, 35(9), 1131‒1142.Google Scholar

Kenny, D. A., & Zautra, A. (1995). The Trait-State-Error Model for Multiwave Data. Journal of Consulting and Clinical Psychology, 63, 52‒59.Google Scholar

Kotov, R., Gamez, W., Schmidt, F., & Watson, D. (2010). Linking “Big” Personality Traits to Anxiety, Depressive, and Substance Use Disorders: A Meta-Analysis. Psychological Bulletin, 136(5), 768‒821.Google Scholar

Lakens, D., Adolfi, F. G., Albers, C. J., Anvari, F., Apps, M. A., Argamon, S. E., … & Buchanan, E. M. (2018). Justify Your Alpha. Nature Human Behaviour, 2(3), 168‒171.Google Scholar

Little, T. D. (2013). Longitudinal Structural Equation Modeling. New York: Guilford Press.Google Scholar

Little, T. D., Lindenberger, U., & Nesselroade, J. R. (1999). On Selecting Indicators for Multivariate Measurement and Modeling Latent Variables: When “Good” Indicators Are Bad and “Bad” Indicators Are Good. Psychological Methods, 4, 192‒211.Google Scholar

Lucas, R. E., & Baird, B. M. (2006). Global Self-Assessment. In Eid, M. & Diener, E. (Eds.), Handbook of Multimethod Measurement in Psychology (pp. 29‒42). Washington, DC: American Psychological Association.Google Scholar

Maxwell, S. E., Kelley, K., & Rausch, J. R. (2008). Sample Size Planning for Statistical Power and Accuracy in Parameter Estimation. Annual Review of Psychology, 59, 537‒563.Google Scholar

Mitchell, T. R., & James, L. R. (2001). Building Better Theory: Time and the Specification of When Things Happen. Academy of Management Review, 26(4), 530‒547.Google Scholar

Mitchell, M. A., & Maxwell, S. E. (2013). A Comparison of the Cross-Sectional and Sequential Designs When Assessing Longitudinal Mediation. Multivariate Behavioral Research, 48(3), 301‒339.Google Scholar

Morton, S. M., Grant, C. C., Carr, P. E. A., Robinson, E. M., Kinloch, J. M., Fleming, C. J., … & Liang, R. (2014). How Do You Recruit and Retain a Prebirth Cohort? Lessons Learnt from Growing Up in New Zealand. Evaluation & the Health Professions, 37(4), 411‒433.Google Scholar

Munafò, M. R., Nosek, B. A., Bishop, D. V., Button, K. S., Chambers, C. D., du Sert, N. P., … & Ioannidis, J. P. (2017). A Manifesto for Reproducible Science. Nature Human Behaviour, 1(1), 0021.Google Scholar

Nelson, L. D., Simmons, J., & Simonsohn, U. (2018). Psychology’s Renaissance. Annual Review of Psychology, 69, 511‒534.Google Scholar

Nosek, B. A., & Bar-Anan, Y. (2012). Scientific Utopia: I. Opening Scientific Communication. Psychological Inquiry, 23(3), 217‒243.Google Scholar

Nosek, B. A., Alter, G., Banks, G. C., Borsboom, D., Bowman, S. D., Breckler, S. J., … & Contestabile, M. (2015). Promoting an Open Research Culture. Science, 348(6242), 1422‒1425.Google Scholar

Nosek, B. A., Ebersole, C. R., DeHaven, A. C., & Mellor, D. T. (2018). The Preregistration Revolution. Proceedings of the National Academy of Sciences, 115, 2600‒2606.Google Scholar

Open Science Collaboration. (2015). Estimating the Reproducibility of Psychological Science. Science, 349(6251), 943‒950.Google Scholar

Paterson, T. A., Harms, P. D., Steel, P., & Credé, M. (2016). An Assessment of the Magnitude of Effect Sizes: Evidence from 30 Years of Meta-Analysis in Management. Journal of Leadership & Organizational Studies, 23(1), 66‒81.Google Scholar

Ram, N., Brinberg, M., Pincus, A. L., & Conroy, D. E. (2017). The Questionable Ecological Validity of Ecological Momentary Assessment: Considerations for Design and Analysis. Research in Human Development, 14(3), 253‒270.Google Scholar

Rast, P., & Hofer, S. M. (2014). Longitudinal Design Considerations to Optimize Power to Detect Variances and Covariances among Rates of Change: Simulation Results Based on Actual Longitudinal Studies. Psychological Methods, 19, 133‒154.Google Scholar

Reise, S. P., Ainsworth, A. T., & Havilan, M. G. (2005). Item Response Theory: Fundamentals, Applications, and Promise in Psychological Research. Current Directions in Psychological Science, 14, 95‒101.Google Scholar

Richard, F. D., Bond, C. F. Jr, & Stokes-Zoota, J. J. (2003). One Hundred Years of Social Psychology Quantitatively Described. Review of General Psychology, 7(4), 331‒363.Google Scholar

Roberts, B. W., & DelVecchio, W. F. (2000). The Rank-Order Consistency of Personality Traits from Childhood to Old Age: A Quantitative Review of Longitudinal Studies. Psychological Bulletin, 126, 3‒25.Google Scholar

Roberts, B. W., Walton, K. E., & Viechtbauer, W. (2006). Patterns of Mean-Level Change in Personality Traits across the Life Course: A Meta-Analysis of Longitudinal Studies. Psychological Bulletin, 132, 1‒25.Google Scholar

Rogosa, D., Brandt, D., & Zimowski, M. (1982). A Growth Curve Approach to the Measurement of Change. Psychological Bulletin, 92, 726‒748.Google Scholar

Schafer, J. L., & Graham, J. W. (2002). Missing Data: Our View of the State of the Art. Psychological Methods, 7, 147‒177.Google Scholar

Schaie, K. W. (1965). A General Model for the Study of Developmental Problems. Psychological Bulletin, 64(2), 92‒107.Google Scholar

Schmitt, N., & Kuljanin, G. (2008). Measurement Invariance: Review of Practice and Implications. Human Resource Management Review, 18(4), 210‒222.Google Scholar

Selig, J. P., & Preacher, K. J. (2009). Mediation Models for Longitudinal Data in Developmental Research. Research in Human Development, 6(2‒3), 144‒164.Google Scholar

Shadish, W. R., Cook, T. D., & Campbell, D. T. (2002). Experimental and Quasi-experimental Designs for Generalized Causal Inference. New York: Houghton Mifflin.Google Scholar

Simmons, J. P., Nelson, L. D., & Simonsohn, U. (2011). False-Positive Psychology: Undisclosed Flexibility in Data Collection and Analysis Allows Presenting Anything as Significant. Psychological Science, 22(11), 1359‒1366.Google Scholar

Simonsohn, U., Nelson, L. D., & Simmons, J. P. (2014). P-Curve: A Key to the File-Drawer. Journal of Experimental Psychology: General, 143(2), 534‒547.Google Scholar

Singer, J. D., & Willett, J. B. (2003). Applied Longitudinal Data Analysis: Modeling Change and Event Occurrence. New York: Oxford University Press.Google Scholar

Smith, G. T., McCarthy, D. M., & Anderson, K. G. (2000). On the Sins of Short-Form Development. Psychological Assessment, 12, 102‒111.Google Scholar

Spellman, B. A., Gilbert, E. A., & Corker, K. S. (2018). Open Science. In Wagenmakers, E. J. & Wixted, J. T. (Eds.), Stevens’ Handbook of Experimental Psychology and Cognitive Neuroscience Volume 5: Methodology (4th edn., Vol. 5, pp. 1‒47). Hoboken, NJ: Wiley.Google Scholar

Steegen, S., Tuerlinckx, F., Gelman, A., & Vanpaemel, W. (2016). Increasing Transparency through a Multiverse Analysis. Perspectives on Psychological Science, 11(5), 702‒712.Google Scholar

Stouthamer-Loeber, M., van Kammen, W., & Loeber, R. (1992). The Nuts and Bolts of Implementing Large-Scale Longitudinal Studies. Violence and Victims, 7, 63‒78.Google Scholar

Tackett, J. L., Lilienfeld, S. O., Patrick, C. J., Johnson, S. L., Krueger, R. F., Miller, J. D., … & Shrout, P. E. (2017). It’s Time to Broaden the Replicability Conversation: Thoughts for and from Clinical Psychological Science. Perspectives on Psychological Science, 12(5), 742‒756.Google Scholar

Taris, T. W. (2000). A Primer in Longitudinal Analysis. Thousand Oaks, CA: Sage.Google Scholar

Timmons, A. C., & Preacher, K. J. (2015). The Importance of Temporal Design: How Do Measurement Intervals Affect the Accuracy and Efficiency of Parameter Estimates in Longitudinal Research? Multivariate Behavioral Research, 50, 41‒55.Google Scholar

Vandenberg, R. J., & Lance, C. E. (2000). A Review and Synthesis of the Measurement Invariance Literature: Suggestions, Practices, and Recommendations for Organizational Research. Organizational Research Methods, 3, 4‒69.Google Scholar

Watson, D. (2004). Stability versus Change, Dependability versus Error: Issues in the Assessment of Personality over Time. Journal of Research in Personality, 38, 319‒350.Google Scholar

Weston, S. J., Ritchie, S. J., Rohrer, J. M., & Przybylski, A. (2018). Recommendations for Increasing the Transparency of Analysis of Pre-existing Datasets. Advances in Methods and Practices in Psychological Science. Retrieved from https://doi.org/10.1177%2F2515245919848684 Google Scholar

Willett, J. B., Singer, J. D., & Martin, N. C. (1998). The Design and Analysis of Longitudinal Studies of Development and Psychopathology in Context: Statistical Models and Methodological Recommendations. Development and Psychopathology, 10, 395‒426.Google Scholar

Wright, A. G. C., & Markon, K. E. (2016). Longitudinal Designs. In Norcross, J. C., VandenBos, G. R., & Freedheim, D. K. (Eds.), American Psychological Association Handbook of Clinical Psychology, Vol. II: Theory and Research (pp. 419‒434). Washington, DC: American Psychological Association.Google Scholar

Wright, A. G., & Zimmermann, J. (2018). Applied Ambulatory Assessment: Integrating Idiographic and Nomothetic Principles of Measurement. Psychological Assessment, November 1. Retrieved from https://doi.org/10.31234/osf.io/6qc5x Google Scholar

Young, A. F., Powers, J. R., & Bell, S. L. (2006). Attrition in Longitudinal Studies: Who Do You Lose? Australian and New Zealand Journal of Public Health, 30(4), 353‒361.Google Scholar

References

Derogatis, F. R. (1975). The Brief Symptom Inventory. Baltimore, MD: Clinical Psychometric Research.Google Scholar

Fu, W. (1998). Penalized Regressions: The Bridge versus the Lasso. Journal of Computational and Graphical Statistics, 7(3), 397‒416.Google Scholar

Gotham, H., Sher, K. J., & Wood, P. K. (1997). Predicting Stability and Change in Frequency of Intoxication from the College Years to Beyond: Individual-Difference and Role Transition Variables. Journal of Abnormal Psychology, 106, 619‒629.Google Scholar

Grekin, E. R., Sher, K. J., & Wood, P. K. (2006). Personality and Substance Dependence Symptoms: Modeling Substance-Specific Traits. Psychology of Addictive Behavior, 20, 415–424.Google Scholar

Jackson, K. M., O’Neill, S. E., & Sher, K. J. (2006). Characterizing Alcohol Dependence: Transitions during Young and Middle Adulthood. Experimental Clinical Psychopharmacology, 14(2), 228‒244.Google Scholar

Jackson, K. M., & Sher, K. J. (2003). Alcohol Use Disorders and Psychological Distress: A Prospective State-Trait Analysis. Journal of Abnormal Psychology, 112, 599‒613.Google Scholar

Jackson, K. M., & Sher, K. J. (2003). Alcohol Use Disorders and Psychological Distress: A Prospective State-Trait Analysis. Journal of Abnormal Psychology, 112(4), 599-613.Google Scholar

Jackson, K. M., Sher, K. J., & Wood, P. K. (2000). Prospective Analyses of Comorbidity: Tobacco and Alcohol Use Disorders. Journal of Abnormal Psychology, 109, 679‒694.Google Scholar

Kutner, M. H., Nachtsheim, C., Neter, J., & Li, W. (2005). Applied Linear Statistical Models. New York: McGraw-Hill Irwin.Google Scholar

McArdle, J. J., & Epstein, D. (1987). Latent Growth Curves within Developmental Structural Equation Models. Child Development, 58(1), 110‒133.Google Scholar

McDonald, R. P. (1967). Nonlinear Factor Analysis. Psychometric Monograph, 15. Richmond, VA: Byrd Press.Google Scholar

Martinez, J. A., Sher, K. J., Krull, J. L., & Wood, P. K. (2009). Blue-Collar Scholars? Mediators and Moderators of University Attrition in First-Generation College Students. Journal of College Student Development, 50(1), 87‒103.Google Scholar

Maydeu-Olivares, A., & Coffman, D.L. (2006). Random Intercept Item Factor Analysis. Psychological Methods, 11, 344‒362.Google Scholar

Meredith, W., & Tisak, J. (1990). Latent Curve Analysis. Psychometrika, 55, 107–122.Google Scholar

Nelson, S., Van Ryzin, M., & Dishion, T. (2015). Alcohol, Marijuana, and Tobacco Use Trajectories from Age 12 to 24 Years: Demographic Correlates and Young Adult Substance Use Problems. Development and Psychopathology, 27(1), 253‒277.Google Scholar

Newsom, J. T. (2015). Longitudinal Structural Equation Modeling: A Comprehensive Introduction. New York: Routledge.Google Scholar

Olsen, M. K., & Schafer, J. L. (2001). A Two-Part Random-Effects Model for Semicontinuous Longitudinal Data. Journal of the American Statistical Association, 96, 730‒745.Google Scholar

Park, A., Sher, K. J., & Krull, J. (2008). Risky Drinking in College Changes as Fraternity/Sorority Affiliation Changes: A Person-Environment Perspective. Psychology of Addictive Behaviors, 22, 219‒229.Google Scholar

Rutledge, P. C., & Sher, K. J. (2001). Heavy Drinking from the Freshman Year into Early Young Adulthood: The Roles of Stress, Tension-Reduction Motives, Sex, and Personality. Journal of Studies on Alcohol, 62, 457‒466.Google Scholar

Savalei, V., & Kolenikov, S. (2008). Constrained versus Unconstrained Estimation in Structural Equation Modeling. Psychological Methods, 13(2), 150‒170.Google Scholar

Sher, K. J., Gotham, H., Erickson, D., & Wood, P. K. (1996a). A Prospective, High-Risk Study of the Relation between Tobacco Dependence and Alcohol Use Disorders. Alcoholism: Clinical and Experimental Research, 20, 485‒492.Google Scholar

Sher, K. J., Wood, M. D., Wood, P. K., & Raskin, G. (1996b). Alcohol Outcome Expectancies and Alcohol Use: A Latent Variable Cross-Lagged Panel Study. Journal of Abnormal Psychology, 105, 561‒574.Google Scholar

Sher, K. J., Wood, P. K., & Gotham, H. (1996c). The Course of Psychological Distress in College: A Prospective High-Risk Study. Journal of College Student Development, 37, 42‒51.Google Scholar

Sher, K. J., Jackson, K. M., & Steinley, D. (2011). Alcohol Use Trajectories and the Ubiquitous Cat’s Cradle: Cause for Concern? Journal of Abnormal Psychology, 120(2), 322‒335.Google Scholar

Simonsohn, U., Simmons, J. P., & Nelson, L. D. (2015). Specification Curve: Descriptive and Inferential Statistics on All Reasonable Specifications. Retrieved from SSRN: https://ssrn.com/abstract=2694998 or http://dx.doi.org/10.2139/ssrn.2694998 Google Scholar

Tucker, L. R. (1958). Determination of Parameters of a Functional Relation by Factor Analysis. Psychometrika, 23, 19–23.Google Scholar

Tucker, L. R. (1966). Learning Theory and Multivariate Experiment: Illustration of Determination of Generalized Learning Curves. In Cattell, R. B. (Ed.), Handbook of Multivariate Experimental Psychology (pp. 476‒501). New York: Rand McNally.Google Scholar

Wiedermann, W., & von Eye, A. (2016). Statistics and Causality: Methods for Applied Empirical Research. Hoboken, NJ: Wiley.Google Scholar

Wohlwill, J. (1973). The Study of Behavioral Development. New York: Academic Press.Google Scholar

Wood, P. K. (2019). Approaches to Understanding Structural Models: Models of Relationships between Variables, Occasions, and People. Seattle, WA: Amazon.Google Scholar

Wood, P. K., Sher, K. J., & Rutledge, P. C. (2007). College Student Alcohol Consumption, Day of the Week, and Class Schedule. Alcoholism: Clinical and Experimental Research, 31, 1195–1207.Google Scholar

Wood, P. K., Steinley, D., & Jackson, K. M. (2015). Right-Sizing Statistical Models for Longitudinal Data. Psychological Methods, 20(4), 470‒488.Google Scholar

Book contents

Part IV - Developmental Psychopathology and Longitudinal Methods

Summary

Access options

References

References

References

References

Recommended Reading

References

References

Save book to Kindle

Save book to Dropbox

Save book to Google Drive