To send content items to your account,
please confirm that you agree to abide by our usage policies.
If this is the first time you use this feature, you will be asked to authorise Cambridge Core to connect with your account.
Find out more about sending content to .
To send content items to your Kindle, first ensure firstname.lastname@example.org
is added to your Approved Personal Document E-mail List under your Personal Document Settings
on the Manage Your Content and Devices page of your Amazon account. Then enter the ‘name’ part
of your Kindle email address below.
Find out more about sending to your Kindle.
Note you can select to send to either the @free.kindle.com or @kindle.com variations.
‘@free.kindle.com’ emails are free but can only be sent to your device when it is connected to wi-fi.
‘@kindle.com’ emails can be delivered even when you are not connected to wi-fi, but note that service fees apply.
This practical book is designed for applied researchers who want to use mixed models with their data. It discusses the basic principles of mixed model analysis, including two-level and three-level structures, and covers continuous outcome variables, dichotomous outcome variables, and categorical and survival outcome variables. Emphasizing interpretation of results, the book develops the most important applications of mixed models, such as the study of group differences, longitudinal data analysis, multivariate mixed model analysis, IPD meta-analysis, and mixed model predictions. All examples are analyzed with STATA, and an extensive overview and comparison of alternative software packages is provided. All datasets used in the book are available for download, so readers can re-analyze the examples to gain a strong understanding of the methods. Although most examples are taken from epidemiological and clinical studies, this book is also highly recommended for researchers working in other fields.
Experimental (longitudinal) studies differ from observational longitudinal studies in that experimental studies (in epidemiology often described as trials) include one or more interventions. In general, before the intervention (i.e. at baseline) the population is (randomly) divided into two or more groups. In the case of two groups, one of the groups receives the intervention of interest and the other group receives a placebo intervention, no intervention at all, or the “usual” treatment. The latter is known as the control group. Both groups are monitored over a certain period of time, in order to find out whether the groups differ with regard to a particular outcome variable. The outcome variable can be continuous, dichotomous, or categorical.
In epidemiology, the simplest form of an experimental longitudinal study is one in which a baseline measurement and only one follow-up measurement are performed (Figure 9.1). If the subjects are randomly assigned to the different groups (interventions), a comparison of the follow-up values between the groups will give an answer to the question of which intervention is more effective with regard to the particular outcome variable. The assumption is that random allocation at baseline will ensure that there is no difference between the groups at baseline (in fact, in this situation a baseline measure is not even necessary).