The purpose of this study is to develop a nonparametric DIF method that (a) compares focal groups directly to the composite group that will be used to develop the reported test score scale, and (b) allows practitioners to explore for DIF related to focal groups stemming from multicategorical variables that constitute a small proportion of the…

The present study aimed to detect the level of faculty members' attitudes at public universities towards the performance appraisal process and its relationship with some variables (gender, college, scientific rank, university, teaching experience, and age). The study sample consisted of (320) faculty members of both sexes in three public…

The purpose of this study is to explore whether there is a statistically significant difference between the ideas of university administrators and faculty members regarding how strictly Educational Performance Indicators for Educators (EPIE) should be monitored in the educational process. The responses of university directors were compared with…

The purpose of this correlational study was to analyze the relationships of various performance variables of pre-service teachers enrolled in a teacher preparation program at Delta State University from fall 2009 to spring 2012. For this group of teacher candidates, the following relationships were analyzed: (a) the significance of the…

Three main purposes provided the foundation for this study. The first purpose was to investigate academic achievement through analyses of data obtained through formal and informal assessments among kindergarten through eighth grade students who participated in a Head Start program, center-based care program, or home-based care prior to school…

Contrary to popular opinion, significance testing does not inform the researcher of the likelihood of the replication of results from current research findings. Result replicability has been ignored by researchers because of an overreliance on significance testing. Several alternatives have been offered to provide the researcher with more…

The various costs of Type I and Type II errors of inference from data are discussed. Six methods for minimizing each error type are presented, which may be employed even after data collection for Type I and which minimizes Type II errors by a study design and analytical means combination. (Author/CM)