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V. N. Vimal Rao; Jeffrey K. Bye; Sashank Varma – Cognitive Research: Principles and Implications, 2024
The 0.05 boundary within Null Hypothesis Statistical Testing (NHST) "has made a lot of people very angry and been widely regarded as a bad move" (to quote Douglas Adams). Here, we move past meta-scientific arguments and ask an empirical question: What is the psychological standing of the 0.05 boundary for statistical significance? We…
Descriptors: Psychological Patterns, Statistical Analysis, Testing, Statistical Significance
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Elliott, Mark; Buttery, Paula – Educational and Psychological Measurement, 2022
We investigate two non-iterative estimation procedures for Rasch models, the pair-wise estimation procedure (PAIR) and the Eigenvector method (EVM), and identify theoretical issues with EVM for rating scale model (RSM) threshold estimation. We develop a new procedure to resolve these issues--the conditional pairwise adjacent thresholds procedure…
Descriptors: Item Response Theory, Rating Scales, Computation, Simulation
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Brauer, Jonathan R.; Day, Jacob C.; Hammond, Brittany M. – Sociological Methods & Research, 2021
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…
Descriptors: Hypothesis Testing, Statistical Analysis, Bayesian Statistics, Statistical Significance
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Jane E. Miller – Numeracy, 2023
Students often believe that statistical significance is the only determinant of whether a quantitative result is "important." In this paper, I review traditional null hypothesis statistical testing to identify what questions inferential statistics can and cannot answer, including statistical significance, effect size and direction,…
Descriptors: Statistical Significance, Holistic Approach, Statistical Inference, Effect Size