Modeling Time-Dependent Association in Longitudinal Data: A Lag as Moderator Approach

被引:51
|
作者
Selig, James P. [1 ]
Preacher, Kristopher J. [2 ]
Little, Todd D. [3 ]
机构
[1] Univ New Mexico, Albuquerque, NM 87131 USA
[2] Vanderbilt Univ, Nashville, TN USA
[3] Univ Kansas, Lawrence, KS 66045 USA
基金
美国国家科学基金会;
关键词
CROSS-SECTIONAL ANALYSES; REGRESSION; MEDIATION; DESIGN; RETEST; BIAS;
D O I
10.1080/00273171.2012.715557
中图分类号
O1 [数学];
学科分类号
0701 ; 070101 ;
摘要
We describe a straightforward, yet novel, approach to examine time-dependent association between variables. The approach relies on a measurement-lag research design in conjunction with statistical interaction models. We base arguments in favor of this approach on the potential for better understanding the associations between variables by describing how the association changes with time. We introduce a number of different functional forms for describing these lag-moderated associations, each with a different substantive meaning. Finally, we use empirical data to demonstrate methods for exploring functional forms and model fitting based on this approach.
引用
收藏
页码:697 / 716
页数:20
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