Testing differences between nested covariance structure models: Power analysis and null hypotheses
Testing differences between nested covariance structure models: Power analysis and null hypotheses
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DOI：
10.1037/1082-989x.11.1.19
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发表时间：
2006-03-01
影响因子：
7
通讯作者：
Cai, L
中科院分区：
文献类型：
--
作者：
MacCallum, RC;Browne, MW;Cai, L
为了比较嵌套协方差结构模型，标准程序是拟合差异的似然比检验，其中零假设是模型在总体中拟合相同。给出了确定该检验统计功效的程序，其中效应量基于模型总体拟合的指定差异。提出了对拟合零差异的标准零假设的修改，允许检验模型之间拟合差异很小而不是零的区间假设。这些发展相结合，产生一个程序，估计功率的检验的一个小的差异，适合与一个备择假设的差异较大的零假设。
For comparing nested covariance structure models, the standard procedure is the likelihood ratio test of the difference in fit, where the null hypothesis is that the models fit identically in the population. A procedure for determining statistical power of this test is presented where effect size is based on a specified difference in overall fit of the models. A modification of the standard null hypothesis of zero difference in fit is proposed allowing for testing an interval hypothesis that the difference in fit between models is small, rather than zero. These developments are combined yielding a procedure for estimating power of a test of a null hypothesis of small difference in fit versus an alternative hypothesis of larger difference.