Standardized coefficients in logistic regression analysis have the same utility as standardized coefficients in linear regression analysis. Although there has been no consensus on the best way to construct standardized logistic regression coefficients, there is now sufficient evidence to suggest a single best approach to the construction of a…

Research examining the relationship between gender and student engagement at the post secondary level has provided mixed results. The current study explores two possible reasons for lack of clarity regarding this relationship: improper parameter estimation resulting from a lack of multi-level analyses and inconsistent conceptions/measures of…

This paper investigates differences in how male and female students perceived a short message service (SMS) library catalog search service when adopting it. Based on a sample of 90 students, the results suggest that there are significant differences in perceived usefulness and intention to use but no significant differences in self-efficacy and…

Multiple regression is commonly used in social and behavioral data analysis. In multiple regression contexts, researchers are very often interested in determining the "best" predictors in the analysis. This focus may stem from a need to identify those predictors that are supportive of theory. Alternatively, the researcher may simply be interested…

The increase in the squared multiple correlation coefficient ([Delta]R[squared]) associated with a variable in a regression equation is a commonly used measure of importance in regression analysis. The coverage probability that an asymptotic and percentile bootstrap confidence interval includes [Delta][rho][squared] was investigated. As expected,…

Limitations of dummy coding and nonsense coding as methods of coding categorical variables for use as predictors in multiple regression analysis are discussed. The combination of these approaches often yields estimates and tests of significance that are not intended by researchers for inclusion in their models. (SLD)

Statistical techniques for identifying exceptional school progress are outlined and illustrated. Regression analyses using two sets of test scores are suggested as a preliminary indicator. These techniques would be useful to school administrators. School progress is best measured by criterion referenced tests rather than norm referenced tests.…

Many outcome variables in developmental psychopathology research are highly stable over time. In conventional longitudinal data analytic approaches such as multiple regression, controlling for prior levels of the outcome variable often yields little (if any) reliable variance in the dependent variable for putative predictors to explain. Three…

Data from the 1986 Current Population Survey (CPS) and a 1987 survey of public and private enterprises in Orangeburg, South Carolina, provide the basis for estimating a salary schedule for lead teachers in Orangeburg School District 5. The underlying rationale for the development of lead teacher positions is described in terms of salary gaps…

The relationship of multiple linear regression to various multivariate statistical techniques is discussed. The importance of the standardized partial regression coefficient (beta weight) in multiple linear regression as it is applied in path, factor, LISREL, and discriminant analyses is emphasized. The multivariate methods discussed in this paper…

An interstate cost-of-living index from SMSA-level market basket data is generated in this research. Models are developed for each of the four regions--Northwest, North Central, South, and West--to explain differences in the cost of living among more than 180 SMSAs. Weighted regression coefficients were combined with comparable state-level data to…