Treating TIME More Flexibly
This chapter demonstrates how to apply the multilevel model to complex data sets. Section 5.1 begins by illustrating what to do when the number of waves is constant but their spacing is irregular. Section 5.2 illustrates what to do when the number of waves per person differs as well; it also discusses the problem of missing data, the most common source of imbalance in longitudinal work. Section 5.3 demonstrates how to include time-varying predictors in your data analysis. Section 5.4 concludes by discussing why and how to adopt alternative representations for the main effect of TIME.
Keywords: multilevel model, time, data analyses, missing data
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