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Beth Chance; Karen McGaughey; Sophia Chung; Alex Goodman; Soma Roy; Nathan Tintle – Journal of Statistics and Data Science Education, 2025
"Simulation-based inference" is often considered a pedagogical strategy for helping students develop inferential reasoning, for example, giving them a visual and concrete reference for deciding whether the observed statistic is unlikely to happen by chance alone when the null hypothesis is true. In this article, we highlight for teachers…
Descriptors: Simulation, Sampling, Randomized Controlled Trials, Hypothesis Testing
Rosa W. Runhardt – Sociological Methods & Research, 2024
This article uses the interventionist theory of causation, a counterfactual theory taken from philosophy of science, to strengthen causal analysis in process tracing research. Causal claims from process tracing are re-expressed in terms of so-called hypothetical interventions, and concrete evidential tests are proposed which are shown to…
Descriptors: Causal Models, Statistical Inference, Intervention, Investigations
Gregory Chernov – Evaluation Review, 2025
Most existing solutions to the current replication crisis in science address only the factors stemming from specific poor research practices. We introduce a novel mechanism that leverages the experts' predictive abilities to analyze the root causes of replication failures. It is backed by the principle that the most accurate predictor is the most…
Descriptors: Replication (Evaluation), Prediction, Scientific Research, Failure
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
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
Per Nilsson; Andreas Eckert – Mathematical Thinking and Learning: An International Journal, 2024
This study contributes to the call for influencing practice by increasing attention to how learning environments can be designed to support learning in statistical inference. We report on a design experiment in secondary school (students 14-16 years old), that resulted in a set of lessons with the learning goal of teaching students how to apply…
Descriptors: Mathematics Instruction, Teaching Methods, Hypothesis Testing, Secondary School Students