文献详情
What Causes the Mean Bias of the Likelihood Ratio Statistic with Many Variables?
文献类型：期刊
期刊名称：Multivariate behavioral research影响因子和分区
年：2019
页码：1-16
ISSN：1532-7906
关键词：Chi-square distribution,best-subset regression,large number of variables,mean bias,small sample size
摘要：Survey data often contain many variables. Structural equation modeling (SEM) is commonly used in analyzing such data. However, conventional SEM methods are not crafted to handle data with a large number of variables (p). A large p can cause Tml, the most widely used likelihood ratio statistic, to depart drastically from the assumed chi-square distribution even with normally distributed data and a relatively large sample size N. A key element affecting this behavior of Tml is its mean bias. The f ...More
Survey data often contain many variables. Structural equation modeling (SEM) is commonly used in analyzing such data. However, conventional SEM methods are not crafted to handle data with a large number of variables (p). A large p can cause Tml, the most widely used likelihood ratio statistic, to depart drastically from the assumed chi-square distribution even with normally distributed data and a relatively large sample size N. A key element affecting this behavior of Tml is its mean bias. The focus of this article is to determine the cause of the bias. To this end, empirical means of Tml via Monte Carlo simulation are used to obtain the empirical bias. The most effective predictors of the mean bias are subsequently identified and their predictive utility examined. The results are further used to predict type I errors of Tml. The article also illustrates how to use the obtained results to determine the required sample size for Tml to behave reasonably well. A real data example is presented to show the effect of the mean bias on model inference as well as how to correct the bias in practice. ...Hide

DOI：10.1080/00273171.2019.1596060
百度学术：What Causes the Mean Bias of the Likelihood Ratio Statistic with Many Variables?
语言：外文
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A Two-level Moderated Latent Variable Model with Single Level Data.Liu Hongyun, Yuan Ke-Hai, Liu Fang,.Multivariate behavioral research. 2019, 1-21.