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Showing 151 to 165 of 3,729 results Save | Export
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Fikis, David R. J.; Oshima, T. C. – Educational and Psychological Measurement, 2017
Purification of the test has been a well-accepted procedure in enhancing the performance of tests for differential item functioning (DIF). As defined by Lord, purification requires reestimation of ability parameters after removing DIF items before conducting the final DIF analysis. IRTPRO 3 is a recently updated program for analyses in item…
Descriptors: Test Bias, Item Response Theory, Statistical Analysis, Computer Software
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Nugent, William R. – Educational and Psychological Measurement, 2017
Meta-analysis is a significant methodological advance that is increasingly important in research synthesis. Fundamental to meta-analysis is the presumption that effect sizes, such as the standardized mean difference (SMD), based on scores from different measures are comparable. It has been argued that population observed score SMDs based on scores…
Descriptors: Meta Analysis, Effect Size, Comparative Analysis, Scores
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Papazoglou, Sofia; Mylonas, Kostas – Educational and Psychological Measurement, 2017
The purpose of this study is to compare alternative multidimensional scaling (MDS) methods for constraining the stimuli on the circumference of a circle and on the surface of a sphere. Specifically, the existing MDS-T method for plotting the stimuli on the circumference of a circle is applied, and its extension is proposed for constraining the…
Descriptors: Multidimensional Scaling, Comparative Analysis, Stimuli, Geometric Concepts
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Chang, Mark – Educational and Psychological Measurement, 2017
We briefly discuss the philosophical basis of science, causality, and scientific evidence, by introducing the hidden but most fundamental principle of science: the similarity principle. The principle's use in scientific discovery is illustrated with Simpson's paradox and other examples. In discussing the value of null hypothesis statistical…
Descriptors: Hypothesis Testing, Evidence, Sciences, Scientific Principles
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Patriota, Alexandre Galvão – Educational and Psychological Measurement, 2017
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…
Descriptors: Hypothesis Testing, Bayesian Statistics, Statistical Inference, Statistical Analysis
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Haig, Brian D. – Educational and Psychological Measurement, 2017
This article considers the nature and place of tests of statistical significance (ToSS) in science, with particular reference to psychology. Despite the enormous amount of attention given to this topic, psychology's understanding of ToSS remains deficient. The major problem stems from a widespread and uncritical acceptance of null hypothesis…
Descriptors: Statistical Significance, Statistical Analysis, Hypothesis Testing, Psychology
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Marsman, Maarten; Wagenmakers, Eric-Jan – Educational and Psychological Measurement, 2017
P values have been critiqued on several grounds but remain entrenched as the dominant inferential method in the empirical sciences. In this article, we elaborate on the fact that in many statistical models, the one-sided "P" value has a direct Bayesian interpretation as the approximate posterior mass for values lower than zero. The…
Descriptors: Bayesian Statistics, Statistical Inference, Probability, Statistical Analysis
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Häggström, Olle – Educational and Psychological Measurement, 2017
Null hypothesis significance testing (NHST) provides an important statistical toolbox, but there are a number of ways in which it is often abused and misinterpreted, with bad consequences for the reliability and progress of science. Parts of contemporary NHST debate, especially in the psychological sciences, is reviewed, and a suggestion is made…
Descriptors: Hypothesis Testing, Statistical Analysis, Psychological Studies, Taxonomy
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Wilcox, Rand R.; Serang, Sarfaraz – Educational and Psychological Measurement, 2017
The article provides perspectives on p values, null hypothesis testing, and alternative techniques in light of modern robust statistical methods. Null hypothesis testing and "p" values can provide useful information provided they are interpreted in a sound manner, which includes taking into account insights and advances that have…
Descriptors: Hypothesis Testing, Bayesian Statistics, Computation, Effect Size
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Park, Ryoungsun; Kim, Jiseon; Chung, Hyewon; Dodd, Barbara G. – Educational and Psychological Measurement, 2017
The current study proposes novel methods to predict multistage testing (MST) performance without conducting simulations. This method, called MST test information, is based on analytic derivation of standard errors of ability estimates across theta levels. We compared standard errors derived analytically to the simulation results to demonstrate the…
Descriptors: Testing, Performance, Prediction, Error of Measurement
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Wiens, Stefan; Nilsson, Mats E. – Educational and Psychological Measurement, 2017
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…
Descriptors: Data Analysis, Effect Size, Computation, Statistical Analysis
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McNeish, Daniel – Educational and Psychological Measurement, 2017
In behavioral sciences broadly, estimating growth models with Bayesian methods is becoming increasingly common, especially to combat small samples common with longitudinal data. Although Mplus is becoming an increasingly common program for applied research employing Bayesian methods, the limited selection of prior distributions for the elements of…
Descriptors: Models, Bayesian Statistics, Statistical Analysis, Computer Software
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Lee, Soo; Bulut, Okan; Suh, Youngsuk – Educational and Psychological Measurement, 2017
A number of studies have found multiple indicators multiple causes (MIMIC) models to be an effective tool in detecting uniform differential item functioning (DIF) for individual items and item bundles. A recently developed MIMIC-interaction model is capable of detecting both uniform and nonuniform DIF in the unidimensional item response theory…
Descriptors: Test Bias, Test Items, Models, Item Response Theory
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Miller, Jeff – Educational and Psychological Measurement, 2017
Critics of null hypothesis significance testing suggest that (a) its basic logic is invalid and (b) it addresses a question that is of no interest. In contrast to (a), I argue that the underlying logic of hypothesis testing is actually extremely straightforward and compelling. To substantiate that, I present examples showing that hypothesis…
Descriptors: Hypothesis Testing, Testing Problems, Test Validity, Relevance (Education)
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García-Pérez, Miguel A. – Educational and Psychological Measurement, 2017
Null hypothesis significance testing (NHST) has been the subject of debate for decades and alternative approaches to data analysis have been proposed. This article addresses this debate from the perspective of scientific inquiry and inference. Inference is an inverse problem and application of statistical methods cannot reveal whether effects…
Descriptors: Hypothesis Testing, Statistical Inference, Effect Size, Bayesian Statistics
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