Previous studies explain situational antecedents of OCB using social exchange theory. However, the effects of factors such as perceptions of job characteristics on OCB seem to require a different explanatory mechanism. We propose that these effects can be explained through a new exchange...

A family of scaling corrections aimed to improve the chi-square approximation of goodness-of-fit test statistics in small samples, large models, and nonnormal data was proposed in Satorra and Bentler (1994). For structural equations models, Satorra-Bentler's (SB) scaling corrections are...

Correlation coefficients have many applications for studying the relationship among multivariate observations. Classical inferences on correlation coefficients are mainly based on the normality assumption. This assumption is hardly realistic in the real world, which implies that the procedures...

Li's pHd method uses an asymptotic chi-squared test statistic to evaluate a hypothesized dimensionality of a reduced-dimension space in a largely nonparametric setting. This statistic is based on an assumed normal distribution of the predictors. When the distributional assumption is violated, a...

Data in social and behavioral sciences are often hierarchically organized. Special statistical procedures have been developed to analyze such data while taking into account the resulting dependence of observations. Most of these developments require a multivariate normality distribution...

Data in social and behavioral sciences are often hierarchically organized. Multilevel statistical methodology was developed to analyze such data. Most of the procedures for analyzing multilevel data are derived from maximum likelihood based on the normal distribution assumption. Standard errors...

The maximum likelihood (ML) method, based on the normal distribution assumption, is widely used in mean and covariance structure analysis. With typical nonnormal data, the ML method will lead to biased statistics and inappropriate scientific conclusions. This article develops a simple but...

Data are called ipsative if they are subject to a constant-sum constraint for each observation. Usually, ipsative data are the consequence of transformation of their corresponding preipsative data. In this article, two kinds of ipsative data are defined. They are the additive ipsative data (AID)...