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…

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…

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…

Progress at NCHEMS is reported on a project to develop indicators of institutional financial condition for higher education institutions. Three steps followed: (1) to develop a framework to reflect dimensions of an institution's financial condition, (2) identification of indicators to measure change in dimensions, and (3) testing of indicators.…

Propensity score analysis is one statistical technique that can be applied to observational data to mimic randomization and thus can be used to estimate causal effects in studies in which the researchers have not applied randomization. In this article the authors (a) describe propensity score methodology and (b) demonstrate its application using…

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)

Described is a method for discriminant analysis which uses the multiple regression facilities offered by many microcomputer statistical packages. This method is illustrated with an ecological example using the MICROTAB statistical package on a BBC microcomputer. Compares these results with an analysis of the same data using SPSS X. (Author/CW)