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Categorisation of input variables for deriving dietary patterns

  • Pierre Traissac (a1) and Yves Martin-Prével (a1)
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1Smith, AD, Emmett, PM, Newby, PK, et al. (2012) Dietary patterns obtained through principal components analysis: the effect of input variable quantification. Br J Nutr (epublication ahead of print version 6 september 2012).
2Newby, PK & Tucker, KL (2004) Empirically derived eating patterns using factor or cluster analysis: a review. Nutr Rev 62, 177203.
3Varraso, R, Garcia-Aymerich, J, Monier, F, et al. (2012) Assessment of dietary patterns in nutritional epidemiology: principal component analysis compared with confirmatory factor analysis. Am J Clin Nutr 96, 10791092.
4Jolliffe, IT (2002) Principal Components Analysis, 2nd ed.New York: Springer.
5Armitage, P & Colton, T (1998) Encyclopedia of Biostatistics. Chichester: Wiley.
6Dodge, Y (2008) The Concise Encyclopedia of Statistics. New York: Springer.
7Turner, EL, Dobson, JE & Pocock, SJ (2010) Categorisation of continuous risk factors in epidemiological publications: a survey of current practice. Epidemiol Perspect Innov 7, 9.
8Bennette, C & Vickers, A (2012) Against quantiles: categorization of continuous variables in epidemiologic research, and its discontents. BMC Med Res Methodol 12, 21.
9Greenacre, MJ (1984) Theory and Applications of Correspondence Analysis. London: Academic Press.
10Sourial, N, Wolfson, C, Bergman, H, et al. (2010) A correspondence analysis revealed frailty deficits aggregate and are multidimensional. J Clin Epidemiol 63, 647654.
11Tessier, S, Traissac, P, Bricas, N, et al. (2010) Food shopping transition: socio-economic characteristics and motivations associated with use of supermarkets in a North African urban environment. Public Health Nutr 13, 14101418.
12Fillol, F, Dubuisson, C, Lafay, L, et al. (2011) Accounting for the multidimensional nature of the relationship between adult obesity and socio-economic status: the French second National Individual Survey on Food Consumption (INCA 2) dietary survey (2006–07). Br J Nutr 106, 16021608.
13Traissac, P & Martin-Prevel, Y (2012) Alternatives to principal components analysis to derive asset-based indices to measure socio-economic position in low- and middle-income countries: the case for multiple correspondence analysis. Int J Epidemiol 41, 12071208, author reply 1209–1210.
14Guinot, C, Latreille, J, Malvy, D, et al. (2001) Use of multiple correspondence analysis and cluster analysis to study dietary behaviour: food consumption questionnaire in the SU.VI.MAX. cohort. Eur J Epidemiol 17, 505516.
15Aounallah-Skhiri, H, Traissac, P, El Ati, J, et al. (2011) Nutrition transition among adolescents of a south-Mediterranean country: dietary patterns, association with socio-economic factors, overweight and blood pressure. A cross-sectional study in Tunisia. Nutr J 10, 38.
16Hoffmann, K, Schulze, MB, Schienkiewitz, A, et al. (2004) Application of a new statistical method to derive dietary patterns in nutritional epidemiology. Am J Epidemiol 159, 935944.

Categorisation of input variables for deriving dietary patterns

  • Pierre Traissac (a1) and Yves Martin-Prével (a1)

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