协变量
多级模型
变量(数学)
变量
多样性(控制论)
考试(生物学)
计算机科学
语法
心理学
线性模型
机器学习
数学
人工智能
生物
数学分析
古生物学
标识
DOI:10.1177/2167696815592726
摘要
Multilevel linear modeling (MLM) is a powerful and well-defined tool often used to evaluate time-varying associations between two or more variables measured in longitudinal studies. Such variables carry information about stable, between-person differences as well as information about within-person variability. For emerging adults, this variability figures prominently across a variety of developmental domains. A single variable measured on repeated occasions can be easily summarized into two new variables that represent the unique within- and between-person sources of information contained in the original variable. Well-known procedures for statistically disaggregating time-varying predictors in an MLM are straightforward but often not accessible to a nontechnical readership. Using SAS syntax, this tutorial provides step-by-step instructions to recode a single repeated-measures variable into separate between- and within-person predictor variables. Strategies are suggested for testing and interpreting main effects and interactions in the MLM, drawing on a daily diary example of first-year, first-time college-attending emerging adults.
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