Uses examples of hierarchical linear modeling (HLM) at local and national levels to illustrate proper applications of HLM and dummy variable regression. Raises cautions about the circumstances under which hierarchical data do not need HLM. (SLD)

An error in an essential equation within the article by Williams and Zimmerman is corrected, and the algebraic inequalities are translated into questions a researcher can ask about simple or residualized difference scores. Williams and Zimmerman acknowledge the error and note that main conclusions are not affected. (SLD)

Observational data were collected over a period of 120 school days from 11 elementary-level, self-contained, learning disabilities classrooms (N=105), using the Student Level Observation of Beginning Reading system. Findings indicate that reliable and unbiased observations of student behavior were obtained through the use of a single observer.…

This paper developed and illustrated a technique to analyze categorical data when subjects can appear in any number of categories for multigroup designs. Post hoc procedures to be used in conjunction with the presented statistical test are also developed. The technique is a large sample technique whose small sample properties are as yet unknown.…

The general class of continuous growth models are described and examples representative of growth models suggested for various types of academic and/or physical growth are given. The fan spread hypothesis is discussed in relationship to natural growth models, as well as differential linear growth. (PN)

A method is developed for testing a priori multiple regression models. The method allows one to specify in advance as many unstandardized or standardized coefficients as one wants to and allows the remaining slopes to be free to vary. (Author/PN)

Results obtained in a metanalysis using indirect alternative methods of computing standardized mean difference effect sizes (SMDESs) were compared with results obtained from direct calculations of SMDESs. In most cases, alternative methods yield very comparable results and are beneficial to use, especially when sample sizes are large. (SLD)

This Monte Carlo study examined the validity of the chi-square test for model evaluation in different instances of misspecification and sample size. The usefulness of the chi-square difference statistic to compare competing structures and improvement in fit is also addressed. (Author/BS)