The effective evaluation of correctional programs is critically important. However, research in corrections rarely allows for the randomization of offenders to conditions of the study. This limitation compromises internal validity, and thus, causal conclusions can rarely be drawn. Increasingly, researchers are employing propensity score matching…

Despite recent emphasis on the use of randomized control trials (RCTs) for evaluating education interventions, in most areas of education research, observational methods remain the dominant approach for assessing program effects. Over the last three decades, the within-study comparison (WSC) design has emerged as a method for evaluating the…

The purpose of this study is to evaluate the views of German teacher trainers working in Turkey about their level regarding Reigeluth's organizational strategies and to analyze their views in terms of gender, geographic region, seniority, and graduated high school variables. While the population of the study consisted of German teacher trainers…

There is currently a considerable diversity of quantitative measures available for summarizing the results in single-case studies. Given that the interpretation of some of them is difficult due to the lack of established benchmarks, the current article proposes an approach for obtaining further numerical evidence on the importance of the results,…

In the context of existing "quantitative"/"qualitative" schisms, this paper briefly reminds readers of the current practice of testing for statistical significance in social science research. This practice is based on a widespread confusion between two conditional probabilities. A worked example and other elements of logical argument demonstrate…

In his article, "An Alternative to Null-Hypothesis Significance Tests," Killeen (2005) urged the discipline to abandon the practice of "p[subscript obs]"-based null hypothesis testing and to quantify the signal-to-noise characteristics of experimental outcomes with replication probabilities. He described the coefficient that he…

The sense that replicability is an important aspect of empirical science led Killeen (2005a) to define "p[subscript rep]," the probability that a replication will result in an outcome in the same direction as that found in a current experiment. Since then, several authors have praised and criticized 'p[subscript rep]," culminating…

This comment offers three descriptions of "p[subscript rep]" that start with a frequentist account of confidence intervals, draw on R. A. Fisher's fiducial argument, and do not make Bayesian assumptions. Links are described among "p[subscript rep]," "p" values, and the probability a confidence interval will capture…

The concept of statistical significance is explained, with specific numerical illustrations. (MNS)

In the educational research literature alpha, the a priori level of significance, and p, the a posteriori probability of obtaining a test statistic of at least a certain value when the null hypothesis is true, are often confused. Explanations for this confusion are offered. Paradoxically, alpha retains a prominent place in textbook discussions of…

This paper presents an index of goodness-of-fit for comparing m models over n trials. The index allows for differentiated weighting of the trials as to their importance in the comparison of the models. Several possible weighting schemes are suggested and the conditions on the weights which assure asymptotic normality of the index distribution are…

This tutorial summarizes some of the widely known limitations of tests of statistical significance and then focuses on extracting measures of variation accounted for as a supplement to significance testing. Two measures of variation accounted for, eta squared and omega squared, are discussed. Computational formulas, computational examples, and…

This paper explains how to combine probabilities from discrete distributions, such as probability distributions for nonparametric tests. (Author/BW)

Remarkability is introduced as a quantifiable attribute of given data and as a basis upon which one may rationally judge its scientific value. Applications of remarkability theory to various research and statistical problems and procedures are discussed. (DG)