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Jorge N. Tendeiro; Rink Hoekstra; Tsz Keung Wong; Henk A. L. Kiers – Teaching Statistics: An International Journal for Teachers, 2025
Most researchers receive formal training in frequentist statistics during their undergraduate studies. In particular, hypothesis testing is usually rooted on the null hypothesis significance testing paradigm and its p-value. Null hypothesis Bayesian testing and its so-called Bayes factor are now becoming increasingly popular. Although the Bayes…
Descriptors: Statistics Education, Teaching Methods, Programming Languages, Bayesian Statistics
Tenko Raykov; Christine DiStefano; Natalja Menold – Structural Equation Modeling: A Multidisciplinary Journal, 2024
This article is concerned with the assumption of linear temporal development that is often advanced in structural equation modeling-based longitudinal research. The linearity hypothesis is implemented in particular in the popular intercept-and-slope model as well as in more general models containing it as a component, such as longitudinal…
Descriptors: Structural Equation Models, Hypothesis Testing, Longitudinal Studies, Research Methodology
Steffen Erickson – Society for Research on Educational Effectiveness, 2024
Background: Structural Equation Modeling (SEM) is a powerful and broadly utilized statistical framework. Researchers employ these models to dissect relationships into direct, indirect, and total effects (Bollen, 1989). These models unpack the "black box" issues within cause-and-effect studies by examining the underlying theoretical…
Descriptors: Structural Equation Models, Causal Models, Research Methodology, Error of Measurement
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
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
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
Ilker Cingillioglu; Uri Gal; Artem Prokhorov – Education and Information Technologies, 2024
This study presents a novel approach contributing to our understanding of the design, development, and implementation AI-based systems for conducting double-blind online randomized controlled trials (RCTs) for higher education research. The process of the entire interaction with the participants (n = 1193) and their allocation to test and control…
Descriptors: Artificial Intelligence, Higher Education, Comparative Analysis, College Choice
Blake H. Heller; Carly D. Robinson – Annenberg Institute for School Reform at Brown University, 2024
Quasi-experimental methods are a cornerstone of applied social science, providing critical answers to causal questions that inform policy and practice. Although open science principles have influenced experimental research norms across the social sciences, these practices are rarely implemented in quasi-experimental research. In this paper, we…
Descriptors: Social Science Research, Research Methodology, Quasiexperimental Design, Scientific Principles
Norah Alsharidi – Journal of Education and Learning, 2025
Educational research enquiries differ based on philosophical beliefs and assumptions regarding researchers' explicitly stated views. This paper critically explores the most dominant philosophical stances in social research sciences, namely positivism, interpretivism and pragmatism. It begins with an overview of the role of the aforementioned…
Descriptors: Educational Research, Social Science Research, Philosophy, Beliefs
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
Bollig, Michael; Schnegg, Michael; Schwieger, Diego A. Menestrey – Field Methods, 2020
This article introduces ethnographic upscaling, an innovative procedure to explore and test hypotheses drawn from in-depth ethnographic findings in spatially continuous cases. The approach combines the strength of localized ethnographic descriptions with questionnaire-based regional surveys to study the distribution of ethnographic findings across…
Descriptors: Ethnography, Anthropology, Research Methodology, Hypothesis Testing
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
Thompson, W. Burt – Teaching of Psychology, 2019
When a psychologist announces a new research finding, it is often based on a rejected null hypothesis. However, if that hypothesis is true, the claim is a false alarm. Many students mistakenly believe that the probability of committing a false alarm equals alpha, the criterion for statistical significance, which is typically set at 5%. Instructors…
Descriptors: Statistical Analysis, Hypothesis Testing, Misconceptions, Data Interpretation
Shen, Zuchao; Curran, F. Chris; You, You; Splett, Joni Williams; Zhang, Huibin – Educational Evaluation and Policy Analysis, 2023
Programs that improve teaching effectiveness represent a core strategy to improve student educational outcomes and close student achievement gaps. This article compiles empirical values of intraclass correlations for designing effective and efficient experimental studies evaluating the effects of these programs. The Early Childhood Longitudinal…
Descriptors: Children, Longitudinal Studies, Surveys, Teacher Empowerment
Hedges, Larry V.; Schauer, Jacob M. – Journal of Educational and Behavioral Statistics, 2019
The problem of assessing whether experimental results can be replicated is becoming increasingly important in many areas of science. It is often assumed that assessing replication is straightforward: All one needs to do is repeat the study and see whether the results of the original and replication studies agree. This article shows that the…
Descriptors: Replication (Evaluation), Research Design, Research Methodology, Program Evaluation