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Cook, Thomas D.; Steiner, Peter M.; Pohl, Steffi – Multivariate Behavioral Research, 2009
This study uses within-study comparisons to assess the relative importance of covariate choice, unreliability in the measurement of these covariates, and whether regression or various forms of propensity score analysis are used to analyze the outcome data. Two of the within-study comparisons are of the four-arm type, and many more are of the…
Descriptors: Statistical Bias, Reliability, Data Analysis, Regression (Statistics)
Markus, Keith A. – Multivariate Behavioral Research, 2008
One can distinguish statistical models used in causal modeling from the causal interpretations that align them with substantive hypotheses. Causal modeling typically assumes an efficient causal interpretation of the statistical model. Causal modeling can also make use of mereological causal interpretations in which the state of the parts…
Descriptors: Research Design, Structural Equation Models, Data Analysis, Causal Models

Keselman, H. J. – Multivariate Behavioral Research, 1982
The need for multiple comparison procedures for repeated measures means employing a pooled estimate of error variance to conform to the sphericity assumptions of the design in order to provide a valid test is discussed. An alternative approach which does not require this assumption is presented. (Author/JKS)
Descriptors: Analysis of Variance, Data Analysis, Hypothesis Testing, Research Design

Huberty, Carl J.; Smith, Jerry D. – Multivariate Behavioral Research, 1982
A particular strategy for investigating effects from a multivariate analysis of variance (MANOVA) is proposed. The strategy involves multiple two-group multivariate analyses. The analysis strategy is described in detail and illustrated with real data sets. (Author/JKS)
Descriptors: Analysis of Variance, Data Analysis, Multivariate Analysis, Research Design

Wiley, James B.; And Others – Multivariate Behavioral Research, 1984
The advantages and disadvantages of balanced incomplete block designs are clarified and their use is demonstrated with an empirical example. A procedure for reducing data of this type to analyzable form is proposed, and an analytical approach that is appropriate for the resulting data is illustrated. (Author/BW)
Descriptors: Behavioral Science Research, Data Analysis, Data Collection, Research Design

Harrop, John W.; Velicer, Wayne F. – Multivariate Behavioral Research, 1985
Computer generated data representative of 16 Auto Regressive Integrated Moving Averages (ARIMA) models were used to compare the results of interrupted time-series analysis using: (1) the known model identification, (2) an assumed (l,0,0) model, and (3) an assumed (3,0,0) model as an approximation to the General Transformation approach. (Author/BW)
Descriptors: Computer Simulation, Data Analysis, Mathematical Models, Matrices

Livert, David; Rindskopf, David; Saxe, Leonard; Stirratt, Mike – Multivariate Behavioral Research, 2001
Describes the application of multilevel statistical models to the evaluation of a multi-site community-based intervention and explicates key issues in the design,analysis, and presentation of results. The initiative described, "Fighting Back, is designed to reduce the demand for illegal drugs and alcohol in a community. (SLD)
Descriptors: Community Programs, Data Analysis, Intervention, Models