Studied Type I error rates and relative power of structural means, multiple-indicator, multiple-cause, and multivariate analysis of variance approaches for testing construct mean differences within a one-factor, two-group design. Used Monte Carlo methods to investigate Type I error rates and a population analysis approach to study the power of…

Recent research using single-stage procedures to test the equality of the means of J independent normal distributions when variances are unequal have proven unsatisfactory in controlling Type I errors and power. A method for dealing with the problem of unequal sample sizes while implementing two-stage procedures is discussed. (TJH)

A Monte Carlo simulation was conducted to study the Type I error rate and power of the 1994 approximation developed by R. A. Alexander and D. M. Govern as an alternative to the analysis of variance "F" test. Conditions under which this test is the best approach are discussed. (SLD)

This study examined the Type I error and power properties of the rank transform test when employed in the context of a balanced 2x2x2 fixed effects analysis of variance (ANOVA). Computer generated Monte Carlo methods were used to compare the Type I error and power properties to those used in the usual test. The results showed the rank transform…

Several methods have been proposed for the analysis of data from single-subject research settings. This research focuses on two methods which have been proposed in previous articles. Criticisms of the methods are presented along with recommendations for practice. (Author/JKS)

Three methods of handling disproportionate cell frequencies in two-way analysis of variance are examined. A Monte Carlo approach was used to study the method of expected frequencies and two multiple regression approaches to the problem as disproportionality increases. (Author/JKS)

This research is an empirical study, through Monte Carlo simulation, of the effects of violations of the assumptions for the oneway fixed-effects analysis of variance (ANOVA) and analysis of covariance (ANCOVA). Research reaffirms findings of previous studies that suggest that ANOVA and ANCOVA be avoided when group sizes are not equal. (SLD)

J. Barnette and J. McLean (1996) proposed a method of controlling Type I error in pairwise multiple comparisons after a significant omnibus F test. This procedure, called Alpha-Max, is based on a sequential cumulative probability accounting procedure in line with Bonferroni inequality. A missing element in the discussion of Alpha-Max was the…

Monte Carlo simulations were used to examine three cases using analyses of variance (ANOVAs) sequentially. Simulation results show that Type I error rates increase when using ANOVAs in this sequential fashion, and the detrimental effect is greatest in situations in which researchers would most likely use ANOVAs sequentially. (SLD)

The paper describes the small sample stability of least square estimates of variance components within the context of generalizability theory. Monte Carlo methods are used to generate data conforming to some selected multifacet generalizability designs to illustrate the sampling behavior of variance component estimates. (Author/CTM)

Used Monte Carlo simulation to determine the psychometric conditions under which differences between raw scores and Rasch transformations of those raw scores are detectable through two-way analysis of variance. Findings demonstrate the inherent inadequacy of untransformed raw scores for two-way analysis of variance. (SLD)

A new approximation is proposed for testing the equality of "k" independent means in the face of heterogeneity of variance. Monte Carlo simulations show that the new procedure has nearly nominal Type I error rates and Type II error rates that are close to those produced by James's second-order approximation. (SLD)

A Monte Carlo study was conducted using the Statistical Analysis System IML computer program to compare the multivariate analysis of variance (MANOVA) simultaneous test procedures of Roy's Greatest Root, the Pillai-Bartlett trace, the Hotelling-Lawley trace, and Wilks' lambda, in terms of power and Type I error under various conditions, including…

Three techniques for estimating Kuder Richardson reliability (KR20) coefficients for incomplete data are contrasted. The methods are: (1) Henderson's Method 1 (analysis of variance, or ANOVA); (2) Henderson's Method 3 (FITCO); and (3) Koch's method of symmetric sums (SYSUM). A Monte Carlo simulation was used to assess the precision of the three…

The problem of determing how many significant discriminant functions are present in a given data set for a one-way, fixed-effects multivariate analysis of variance design is studied using a Monte Carlo procedure. A variety of procedures, including the popular partitioned-U procedure, are compared with respect to their Type I error rates and power…