EXAMINING CHANGE USING REGRESSION-ANALYSIS - 3 APPROACHES COMPARED
EXAMINING CHANGE USING REGRESSION-ANALYSIS - 3 APPROACHES COMPARED
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DOI：
10.1080/02732173.1991.9981960
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发表时间：
1991-01-01
影响因子：
1.8
通讯作者：
WILLITS, FK
中科院分区：
文献类型：
--
作者：
DALECKI, M;WILLITS, FK
尽管社会科学家经常面临评估变化相关因素的任务，但这样做的方法却常常被误解。该分析比较了使用回归程序处理此任务的三种方法：（a）变化或差异分数（Time2-Time1[T2-T1]作为因变量，T1score作为协变量；（b）T2score作为因变量，T1分数作为协变量；（c）残差T2score作为因变量。所有这些都显示出对实质性变量和变化之间关系的相同解释。然而，我们认为使用作为因变量的差异分数通常是更可取的（当 T1 时，分数受到控制），因为结果分析直接处理调整后的变化。
Although social scientists are frequently faced with the task of assessing the correlates of change, the methods for doing so are often misunderstood. This analysis compares three approaches for dealing with this task using regression procedures: (a) change or difference score (Time2‐ Time1[T2‐ T1] as the dependent variable with T1score included as a covariate; (b) T2score as the dependent variable and T1, score as a covariate; and (c) residualized T2score as the dependent variable. All are shown to result in identical interpretations of the relationship between substantive variables and change. We argue, however, that the use of difference scores as the dependent variable is generally preferable (when T1, score is controlled) because the resulting analysis deals directly with adjusted change.