A causal model of halo error (HE) is derived. Three hypotheses are formulated to explain findings of negative HE. It is suggested that apparent negative HE may have been misinferred from existing correlational measures of HE, and that positive HE is more prevalent than had previously been thought. (SLD)

Analysis of covariance (ANCOVA) is a data analysis method that is often used to control extraneous sources of variation in non-equivalent group designs. It is commonly believed that as long as the covariate is highly correlated with the dependent variable there is nothing to lose in using ANCOVA, even in non-randomized studies. This paper examines…

Although analysis of covariance (ANCOVA) is used fairly infrequently in published research, the method is used much more frequently in dissertations and in evaluation research. This paper reviews the assumptions that must be met for ANCOVA to yield useful results, and argues that ANCOVA will yield distorted and inaccurate results when these…

The analysis of covariance as a procedure for statistical correction of the effects for an extraneous variable, called a "covariate," is presented. An heuristic data set is used to make the discussion of the calculation of ANCOVA partitions easier to follow. A discussion of homogeneity of regression as an essential condition to be met…

This repeated measures factorial design study compared the results of two procedures for identifying multivariate outliers under varying conditions, the Mahalanobis distance and the Andrews-Pregibon statistic. Results were analyzed for the total number of outliers identified and number of false outliers identified. Simulated data were limited to…

The uses and restrictions of commonality analysis are described. Commonality analysis has been increasingly used as a method to examine the relative importance of independent variables, through the partitioning of variance among the variables of the regression equation into unique and common components. The effects of all other independent…

An equation was derived to determine the relationship between the pooled within-subgroup r (correlation coefficient) and the r obtained from the total group data. It was, thus, possible to assess the amount of distortion introduced by pooling heterogeneous subgroups. As a basis for deciding whether to pool two subgroups in order to calculate a…

The overidentification of structural equation models with latent variables is discussed. The use of two- and three-indicator models is not recommended since such models do not allow a testing of the crucial assumption of unidimensionality among indicators in most cases. Models with four or more indicators may be more sensitive to departures from…

Problems associated with the analysis of data collected using the Solomon Four Group Design are discussed. The design includes an experimental group and a control group that have been pretested and posttested, and an experimental and a control group that have been posttested only. A sample problem is approached in three different ways. First, the…

The problem of model estimation when the data are collinear was examined. Though the ridge regression (RR) outperforms ordinary least squares (OLS) regression in the presence of acute multicollinearity, it is not a problem free technique for reducing the variance of the estimates. It is a stochastic procedure when it should be nonstochastic and it…

The effects of using different data analysis methods on estimates of treatment effects of educational programs were investigated. Various regression models, such as those recommended for Title I program evaluations, were studied. The first effect studied was the amount of bias that might be expected to occur in the various settings. Results…

This paper provides an up-to-date review of the relationship between item response theory (IRT) and (nonlinear) common factor theory and draws out of this relationship some implications for current and future research in IRT. Nonlinear common factor analysis yields a natural embodiment of the weak principle of local independence in appropriate…

A study was undertaken to develop guidelines for the interpretation of the parameters of three multidimensional item response theory models and to determine the relationship between the parameters and traditional concepts of item difficulty and discrimination. The three models considered were multidimensional extensions of the one-, two-, and…

This paper describes an analytical solution to a common problem in aptitude-treatment interaction (ATI). The researcher is often interested in the comparison between treatments for a large set of attributes. If this set is large, the chance of non-orthogonality is correspondingly large. In these circumstances the analysis and interpretation…

The purpose of this research study was to assess item response model-test data fit using residuals. First, a comparison of raw and standardized residuals for describing model-test data fit was carried out. Second, hypotheses concerning the relationship between residual sizes and several item characteristics were studied. The analyses with…