Researchers often have hypotheses concerning the state of affairs in the population from which they sampled their data to compare group means. The classical frequentist approach provides one way of carrying out hypothesis testing using ANOVA to state the null hypothesis that there is no difference in the means and proceed with multiple comparisons…

In late November 2020, there was a flurry of media coverage of two companies' claims of 95% efficacy rates of newly developed COVID-19 vaccines, but information about the confidence interval was not reported. This paper presents a way of teaching the concept of hypothesis testing and the construction of confidence intervals using numbers announced…

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…

The present study proposes a Bayesian approach for estimating and testing the operation-specific learning model, a variant of the linear logistic test model that allows for the measurement of the learning that occurs during a test as a result of the repeated use of the operations involved in the items. The advantages of using a Bayesian framework…

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…

According to Wollack and Schoenig (2018), score differencing is one of six types of statistical methods used to detect test fraud. In this paper, we suggested the use of Bayes factors (e.g., Kass & Raftery, 1995) for score differencing. A simulation study shows that the suggested approach performs slightly better than an existing frequentist…

BASIE is a framework for interpreting impact estimates from evaluations. It is an alternative to null hypothesis significance testing. This guide walks researchers through the key steps of applying BASIE, including selecting prior evidence, reporting impact estimates, interpreting impact estimates, and conducting sensitivity analyses. The guide…

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…

Bayesian and classical statistical approaches are based on different types of logical principles. In order to avoid mistaken inferences and misguided interpretations, the practitioner must respect the inference rules embedded into each statistical method. Ignoring these principles leads to the paradoxical conclusions that the hypothesis…

Statistical mediation allows researchers to investigate potential causal effects of experimental manipulations through intervening variables. It is a powerful tool for assessing the presence and strength of postulated causal mechanisms. Although mediation is used in certain areas of psychology, it is rarely applied in cognitive psychology and…

Because of the continuing debates about statistics, many researchers may feel confused about how to analyze and interpret data. Current guidelines in psychology advocate the use of effect sizes and confidence intervals (CIs). However, researchers may be unsure about how to extract effect sizes from factorial designs. Contrast analysis is helpful…

The null hypothesis test used in differential item functioning (DIF) detection tests for a subgroup difference in item-level performance--if the null hypothesis of "no DIF" is rejected, the item is flagged for DIF. Conversely, an item is kept in the test form if there is insufficient evidence of DIF. We present frequentist and empirical…

To begin statistical analysis, Bayesians quantify their confidence in modeling hypotheses with priors. A prior describes the probability of a certain modeling hypothesis apart from the data. Bayesians should be able to defend their choice of prior to a skeptical audience. Collaboration between evaluators and stakeholders could make their choices…

Although advances have improved our ability to describe the measurement precision of a test, it often remains challenging to summarize how well a test is performing overall. Reliability, for example, provides an overall summary of measurement precision, but it is sample-specific and might not reflect the potential usefulness of a test if the…

This inquiry is an investigation of item response theory (IRT) proficiency estimators' accuracy under multistage testing (MST). We chose a two-stage MST design that includes four modules (one at Stage 1, three at Stage 2) and three difficulty paths (low, middle, high). We assembled various two-stage MST panels (i.e., forms) by manipulating two…