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Xiao Liu; Zhiyong Zhang; Lijuan Wang – Grantee Submission, 2024
In psychology, researchers are often interested in testing hypotheses about mediation, such as testing the presence of a mediation effect of a treatment (e.g., intervention assignment) on an outcome via a mediator. An increasingly popular approach to testing hypotheses is the Bayesian testing approach with Bayes factors (BFs). Despite the growing…
Descriptors: Sample Size, Bayesian Statistics, Programming Languages, Simulation
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Shunji Wang; Katerina M. Marcoulides; Jiashan Tang; Ke-Hai Yuan – Structural Equation Modeling: A Multidisciplinary Journal, 2024
A necessary step in applying bi-factor models is to evaluate the need for domain factors with a general factor in place. The conventional null hypothesis testing (NHT) was commonly used for such a purpose. However, the conventional NHT meets challenges when the domain loadings are weak or the sample size is insufficient. This article proposes…
Descriptors: Hypothesis Testing, Error of Measurement, Comparative Analysis, Monte Carlo Methods
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Caspar J. Van Lissa; Eli-Boaz Clapper; Rebecca Kuiper – Research Synthesis Methods, 2024
The product Bayes factor (PBF) synthesizes evidence for an informative hypothesis across heterogeneous replication studies. It can be used when fixed- or random effects meta-analysis fall short. For example, when effect sizes are incomparable and cannot be pooled, or when studies diverge significantly in the populations, study designs, and…
Descriptors: Hypothesis Testing, Evaluation Methods, Replication (Evaluation), Sample Size
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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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Xu, Jun; Bauldry, Shawn G.; Fullerton, Andrew S. – Sociological Methods & Research, 2022
We first review existing literature on cumulative logit models along with various ways to test the parallel lines assumption. Building on the traditional frequentist framework, we introduce a method of Bayesian assessment of null values to provide an alternative way to examine the parallel lines assumption using highest density intervals and…
Descriptors: Bayesian Statistics, Evaluation Methods, Models, Intervals
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Blair P. Lloyd; Jessica N. Torelli; Marney S. Pollack; Emily S. Weaver – Journal of Behavioral Education, 2024
For students with severe or complex challenging behavior, incorporating hypothesis testing as a component of functional behavior assessment (FBA) is often warranted. Several hypothesis testing strategies (i.e., functional analysis, antecedent analysis, concurrent operant analysis) can confirm whether and how features of a student's environment…
Descriptors: Behavior Disorders, Severe Disabilities, Functional Behavioral Assessment, Environmental Influences
Elizabeth Talbott; Andres De Los Reyes; Devin M. Kearns; Jeannette Mancilla-Martinez; Mo Wang – Exceptional Children, 2023
Evidence-based assessment (EBA) requires that investigators employ scientific theories and research findings to guide decisions about what domains to measure, how and when to measure them, and how to make decisions and interpret results. To implement EBA, investigators need high-quality assessment tools along with evidence-based processes. We…
Descriptors: Evidence Based Practice, Evaluation Methods, Special Education, Educational Research
Blair P. Lloyd; Jessica N. Torelli; Marney S. Pollack; Emily S. Weaver – Grantee Submission, 2022
For students with severe or complex challenging behavior, incorporating hypothesis testing as a component of functional behavior assessment (FBA) is often warranted. Several hypothesis testing strategies (i.e., functional analysis, antecedent analysis, concurrent operant analysis) can confirm whether and how features of a student's environment…
Descriptors: Behavior Disorders, Severe Disabilities, Functional Behavioral Assessment, Environmental Influences
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Barrenechea, Rodrigo; Mahoney, James – Sociological Methods & Research, 2019
This article develops a set-theoretic approach to Bayes's theorem and Bayesian process tracing. In the approach, hypothesis testing is the procedure whereby one updates beliefs by narrowing the range of states of the world that are regarded as possible, thus diminishing the domain in which the actual world can reside. By explicitly connecting…
Descriptors: Bayesian Statistics, Hypothesis Testing, Qualitative Research, Research Methodology
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Deke, John; Finucane, Mariel; Thal, Daniel – National Center for Education Evaluation and Regional Assistance, 2022
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…
Descriptors: Bayesian Statistics, Educational Research, Data Interpretation, Hypothesis Testing
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Porter, Kristin E. – Society for Research on Educational Effectiveness, 2016
In recent years, there has been increasing focus on the issue of multiple hypotheses testing in education evaluation studies. In these studies, researchers are typically interested in testing the effectiveness of an intervention on multiple outcomes, for multiple subgroups, at multiple points in time or across multiple treatment groups. When…
Descriptors: Hypothesis Testing, Intervention, Error Patterns, Evaluation Methods
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Lortie-Forgues, Hugues; Inglis, Matthew – Educational Researcher, 2019
In this response, we first show that Simpson's proposed analysis answers a different and less interesting question than ours. We then justify the choice of prior for our Bayes factors calculations, but we also demonstrate that the substantive conclusions of our article are not substantially affected by varying this choice.
Descriptors: Randomized Controlled Trials, Bayesian Statistics, Educational Research, Program Evaluation
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Yang, Shitao; Black, Ken – Teaching Statistics: An International Journal for Teachers, 2019
Summary Employing a Wald confidence interval to test hypotheses about population proportions could lead to an increase in Type I or Type II errors unless the hypothesized value, p0, is used in computing its standard error rather than the sample proportion. Whereas the Wald confidence interval to estimate a population proportion uses the sample…
Descriptors: Error Patterns, Evaluation Methods, Error of Measurement, Measurement Techniques
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Marmolejo-Ramos, Fernando; Cousineau, Denis – Educational and Psychological Measurement, 2017
The number of articles showing dissatisfaction with the null hypothesis statistical testing (NHST) framework has been progressively increasing over the years. Alternatives to NHST have been proposed and the Bayesian approach seems to have achieved the highest amount of visibility. In this last part of the special issue, a few alternative…
Descriptors: Hypothesis Testing, Bayesian Statistics, Evaluation Methods, Statistical Inference
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Butler, Michelle A.; Katayama, Andrew D.; Schindling, Casey; Dials, Katherine – Journal of Educational Research, 2018
Although testing accommodations for standardized assessments are available for students with disabilities, interpretation remains challenging. The authors explored resilience to see if it could contribute to the interpretation of academic success for students who are deaf or hard of hearing or blind or have low vision. High school students (30…
Descriptors: Deafness, Blindness, Resilience (Psychology), Student Evaluation
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