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Vaske, Jerry J. – Sagamore-Venture, 2019
Data collected from surveys can result in hundreds of variables and thousands of respondents. This implies that time and energy must be devoted to (a) carefully entering the data into a database, (b) running preliminary analyses to identify any problems (e.g., missing data, potential outliers), (c) checking the reliability and validity of the…
Descriptors: Surveys, Theories, Hypothesis Testing, Effect Size
Warne, Russell T. – Practical Assessment, Research & Evaluation, 2014
Reviews of statistical procedures (e.g., Bangert & Baumberger, 2005; Kieffer, Reese, & Thompson, 2001; Warne, Lazo, Ramos, & Ritter, 2012) show that one of the most common multivariate statistical methods in psychological research is multivariate analysis of variance (MANOVA). However, MANOVA and its associated procedures are often not…
Descriptors: Multivariate Analysis, Behavioral Science Research, Discriminant Analysis, Psychological Studies
McGee, Jennifer – 2000
Both predictive discriminant analysis (PDA) and descriptive discriminant analysis (DDA) require a decision to pool group covariance matrices, or alternatively, to retain separate group covariance matrices when the group covariance matrices are too dissimilar to pool. Pooling the group covariance matrices involves the so-called "linear"…
Descriptors: Discriminant Analysis, Multivariate Analysis
Strang, Kenneth David – Practical Assessment, Research & Evaluation, 2009
This paper discusses how a seldom-used statistical procedure, recursive regression (RR), can numerically and graphically illustrate data-driven nonlinear relationships and interaction of variables. This routine falls into the family of exploratory techniques, yet a few interesting features make it a valuable compliment to factor analysis and…
Descriptors: Multicultural Education, Computer Software, Multiple Regression Analysis, Multidimensional Scaling
Huberty, Carl J.; Smith, Jerry D. – 1981
A particular strategy for investigating effects resulting from a multivariate analysis of variance (MANOVA) is proposed. The strategy involves multiple two-group multivariate analyses. The two groups result from considering multivariate pairwise group contrasts or multivariate complex group contrasts. Assuming a given two-group analysis yields…
Descriptors: Analysis of Variance, Comparative Analysis, Discriminant Analysis, Hypothesis Testing
Strand, Kenneth H. – Online Submission, 2000
This paper contains information concerning the following: 1. An overview of multivariate analysis of variance, and discriminant (DA) and canonical (CA) analyses. 2. An introduction to specification and measurement errors, and collinearity. 3. The sparsity of information concerning specification and measurement errors and collinearity as they…
Descriptors: Multivariate Analysis, Multiple Regression Analysis, Discriminant Analysis, Error of Measurement
Dzhafarov, Ehtibar N.; Colonius, Hans – Psychometrika, 2006
We describe a principled way of imposing a metric representing dissimilarities on any discrete set of stimuli (symbols, handwritings, consumer products, X-ray films, etc.), given the probabilities with which they are discriminated from each other by a perceiving system, such as an organism, person, group of experts, neuronal structure, technical…
Descriptors: Psychometrics, Stimuli, Probability, Discriminant Analysis
Kristjansson, Elizabeth; Aylesworth, Richard; Mcdowell, Ian; Zumbo, Bruno D. – Educational and Psychological Measurement, 2005
Item bias is a major threat to measurement validity. Methods for detecting differential item functioning (DIF) are now commonly used to identify potentially biased items. DIF detection methods for dichotomous items are well developed, but those for ordinal items are less well developed. In this article, the authors compare four methods for…
Descriptors: Discriminant Analysis, Test Bias, Multivariate Analysis, Regression (Statistics)
Van Epps, Pamela D. – 1987
This paper discusses the principles underlying discriminant analysis and constructs a simulated data set to illustrate its methods. Discriminant analysis is a multivariate technique for identifying the best combination of variables to maximally discriminate between groups. Discriminant functions are established on existing groups and used to…
Descriptors: Classification, Correlation, Discriminant Analysis, Educational Research

Sullins, Walter L. – Contemporary Education, 1983
This paper comments on the impact of computers on statistical analysis and presents a concise, nontechnical overview of five statistical methods now being applied in educational research. Appropriate uses of these techniques are pointed out, along with dangers concerning misapplications. (PP)
Descriptors: Comparative Analysis, Computer Programs, Discriminant Analysis, Educational Research