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Boyajian, Jonathan – Online Submission, 2011
This conference presentation reviews the authors' work on autocorrelations in single-case designs. The bias-corrected autocorrelation is computed, results are meta-analyzed with 5-level multilevel analysis in SAS Proc Mixed. Results suggest autocorrelations are normally distributed, and that taking into account nesting in outcomes and articles…
Descriptors: Correlation, Research Design, Meta Analysis, Statistical Distributions
Lix, Lisa M.; Keselman, H. J. – 1995
Tests of mean equality proposed by Alexander and Govern (1994) and Tsakok (1978) were compared to the well-known procedures of Brown and Forsythe (1974), James (1951), and Welch (1951) for their ability to limit the number of Type I errors in one-way designs where the underlying distributions were nonnormal, variances were nonhomogeneous, and…
Descriptors: Comparative Analysis, Estimation (Mathematics), Foreign Countries, Least Squares Statistics

Graham, John W.; And Others – Multivariate Behavioral Research, 1996
The utility of the three-form design coupled with maximum likelihood methods for estimation of missing values was evaluated. Simulation studies demonstrate that maximum likelihood estimation and multiple imputation methods produce the most efficient and least biased estimates of variances and covariances for normally distributed and slightly…
Descriptors: Data Collection, Estimation (Mathematics), Maximum Likelihood Statistics, Research Design

Olejnik, Stephen F.; Algina, James – 1985
This paper examined the rank transformation approach to analysis of variance as a solution to the Behrens-Fisher problem. Using simulation methodology four parameters were manipulated for the two group design: (1) ratio of population variances; (2) distribution form; (3) sample size and (4) population mean difference. The results indicated that…
Descriptors: Analysis of Variance, Computer Simulation, Error of Measurement, Hypothesis Testing
Wu, Yi-Cheng; McLean, James E. – 1993
By employing a concomitant variable, researchers can reduce the error, increase the precision, and maximize the power of an experimental design. Blocking and analysis of covariance (ANCOVA) are most often used to harness the power of a concomitant variable. Whether to block or covary and how many blocks to be used if a block design is chosen…
Descriptors: Analysis of Covariance, Analysis of Variance, Computer Simulation, Correlation
Johnson, Colleen Cook – 1993
The purpose of this study is to help define the precise nature and limits of the tolerable range in which a researcher may be relatively confident about the statistical validity of his or her research findings, focusing specifically on the statistical validity of results when violating the assumptions associated with the one-way, fixed-effects…
Descriptors: Analysis of Covariance, Analysis of Variance, Comparative Analysis, Computer Simulation
Santmire, Toni E. – 1984
The purpose of this paper is to discuss ways in which developmental psychology suffers from the lack of an appropriate technology of measurement and statistical analysis. The paper begins by noting that developmental psychology is the study of change; that individuals develop through a succession of "stages" which are separated by…
Descriptors: Data Analysis, Data Collection, Developmental Psychology, Developmental Stages