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Widaman, Keith F. – Educational and Psychological Measurement, 2023
The import or force of the result of a statistical test has long been portrayed as consistent with deductive reasoning. The simplest form of deductive argument has a first premise with conditional form, such as p[right arrow]q, which means that "if p is true, then q must be true." Given the first premise, one can either affirm or deny…
Descriptors: Hypothesis Testing, Statistical Analysis, Logical Thinking, Probability
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Nobuyuki Hanaki; Jan R. Magnus; Donghoon Yoo – Journal of Statistics and Data Science Education, 2023
Common sense is a dynamic concept and it is natural that our (statistical) common sense lags behind the development of statistical science. What is not so easy to understand is why common sense lags behind as much as it does. We conduct a survey among Japanese students and provide examples and tentative explanations of a number of statistical…
Descriptors: Statistics, Statistics Education, Epistemology, Statistical Analysis
Chenchen Ma; Gongjun Xu – Grantee Submission, 2022
Cognitive Diagnosis Models (CDMs) are a special family of discrete latent variable models widely used in educational, psychological and social sciences. In many applications of CDMs, certain hierarchical structures among the latent attributes are assumed by researchers to characterize their dependence structure. Specifically, a directed acyclic…
Descriptors: Vertical Organization, Models, Evaluation, Statistical Analysis
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Levin, Joel R.; Ferron, John M.; Gafurov, Boris S. – Educational Psychology Review, 2021
Previous simulation studies of randomization tests applied in single-case educational intervention research contexts have typically focused on A-to-B phase changes in means/levels. In the present simulation study, we report the results of two multiple-baseline investigations, one targeting between-phase changes in slopes/trends and the other…
Descriptors: Educational Research, Statistical Analysis, Hypothesis Testing, Intervention
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Tan, Teck Kiang – Practical Assessment, Research & Evaluation, 2023
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…
Descriptors: Comparative Analysis, Hypothesis Testing, Statistical Analysis, Guidelines
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Johnson, Roger W. – Journal of Statistics and Data Science Education, 2022
For ease of instruction in the classroom, the one-way analysis of variance F statistic is rewritten in terms of pairwise differences in individual sample means instead of differences of individual sample means from the overall sample mean. Likewise, the Kruskal-Wallis statistic may be rewritten in terms of pairwise differences in individual…
Descriptors: Statistics Education, Statistical Analysis, Hypothesis Testing, Sampling
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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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Finch, W. Holmes – Journal of Experimental Education, 2022
Multivariate analysis of variance (MANOVA) is widely used to test the null hypothesis of equal multivariate means across 2 or more groups. MANOVA rests upon an assumption that error terms are independent of one another, which can be violated if individuals are clustered or nested within groups, such as schools. Ignoring such nesting can result in…
Descriptors: Multivariate Analysis, Hypothesis Testing, Structural Equation Models, Hierarchical Linear Modeling
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Guastadisegni, Lucia; Cagnone, Silvia; Moustaki, Irini; Vasdekis, Vassilis – Educational and Psychological Measurement, 2022
This article studies the Type I error, false positive rates, and power of four versions of the Lagrange multiplier test to detect measurement noninvariance in item response theory (IRT) models for binary data under model misspecification. The tests considered are the Lagrange multiplier test computed with the Hessian and cross-product approach,…
Descriptors: Measurement, Statistical Analysis, Item Response Theory, Test Items
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Lund, Thorleif – Scandinavian Journal of Educational Research, 2022
Criteria are briefly proposed for final conclusions, research problems, and research hypotheses in quantitative research. Moreover, based on a proposed definition of applied and basic/general research, it is argued that (1) in applied quantitative research, while research problems are necessary, research hypotheses are unjustified, and that (2) in…
Descriptors: Research Problems, Research Methodology, Hypothesis Testing, Statistical Analysis
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Vembye, Mikkel Helding; Pustejovsky, James Eric; Pigott, Therese Deocampo – Journal of Educational and Behavioral Statistics, 2023
Meta-analytic models for dependent effect sizes have grown increasingly sophisticated over the last few decades, which has created challenges for a priori power calculations. We introduce power approximations for tests of average effect sizes based upon several common approaches for handling dependent effect sizes. In a Monte Carlo simulation, we…
Descriptors: Meta Analysis, Robustness (Statistics), Statistical Analysis, Models
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Clintin P. Davis-Stober; Jason Dana; David Kellen; Sara D. McMullin; Wes Bonifay – Grantee Submission, 2023
Conducting research with human subjects can be difficult because of limited sample sizes and small empirical effects. We demonstrate that this problem can yield patterns of results that are practically indistinguishable from flipping a coin to determine the direction of treatment effects. We use this idea of random conclusions to establish a…
Descriptors: Research Methodology, Sample Size, Effect Size, Hypothesis Testing
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Hertog, Steffen – Sociological Methods & Research, 2023
In mixed methods approaches, statistical models are used to identify "nested" cases for intensive, small-n investigation for a range of purposes, including notably the examination of causal mechanisms. This article shows that under a commonsense interpretation of causal effects, large-n models allow no reliable conclusions about effect…
Descriptors: Case Studies, Generalization, Prediction, Mixed Methods Research
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Frank Wang – Numeracy, 2021
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…
Descriptors: COVID-19, Pandemics, Immunization Programs, Hypothesis Testing
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Nikolakopoulos, Stavros – Research Synthesis Methods, 2020
In narrative synthesis of evidence, it can be the case that the only quantitative measures available concerning the efficacy of an intervention is the direction of the effect, that is, whether it is positive or negative. In such situations, the sign test has been proposed in the literature and in recent Cochrane guidelines as a way to test whether…
Descriptors: Synthesis, Evidence, Statistical Analysis, Nonparametric Statistics
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