This article presents two alternative methods to null hypothesis significance testing (NHST) for improving inferences from underpowered research designs. Post hoc design analysis (PHDA) assesses whether an NHST analysis generating null findings might otherwise have had sufficient power to detect effects of plausible magnitudes. Bayesian analysis…

Purpose: Null hypothesis significance testing is commonly used in audiology research to determine the presence of an effect. Knowledge of study outcomes, including nonsignificant findings, is important for evidence-based practice. Nonsignificant "p" values obtained from null hypothesis significance testing cannot differentiate between…

Purpose: Evidence-based data analysis methods are important in clinical research fields, including speech-language pathology and audiology. Although commonly used, null hypothesis significance testing (NHST) has several limitations with regard to the conclusions that can be drawn from results, particularly nonsignificant findings. Bayes factors…

A numerical procedure is outlined for obtaining an interval estimate of true score. The procedure is applied to several sets of test data. (Author)

Statistical significance is not a sufficient condition for claiming a hypothesis has been supported. Constructive replications are more important. Statistically significant results may be meaningless while a sequence of nonsignificant results may be quite important. Gives advice on how to overcome some limitations of classifical statistical…

This article compares three models that have been the foundation for approaches to the analysis of statistical significance in early childhood research--the Fisherian and the Neyman-Pearson models (both considered "classical" approaches), and the Bayesian model. The article concludes that all three models have a place in the analysis of research…

A linear classification rule (used with equal covariance matrices) was contrasted with a quadratic rule (used with unequal covariance matrices) for accuracy of internal and external classification. The comparisons were made for seven situations which resulted from combining three data conditions (equal and unequal covariance matrices, minimal and…

Despite advances in common factor analysis, a review of 89 studies published in four selected journals between 1963 and 1976 indicated that behavioral scientists preferred principal components analysis, followed by varimax or orthogonal rotation. Resultant row sums of squares of factor matrices from principal component analyses of real data sets…

Unlike the past models guiding cross-cultural psychological research, a new paradigm facilitates multiple level investigations by incorporating both culture-specific (nested) and culture-general (crossed) independent variables within its partially-hierarchical framework. Based upon the generalizability analysis, this model generates sequential…