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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
Samantha Mann; Aldert Vrij; Haneen Deeb – Applied Cognitive Psychology, 2024
We examined the efficacy of a Model Statement to detect opinion lies. A total of 93 participants discussed their opinion about the recent strikes on two occasions, 1 week apart. In one interview they told the truth and in the other interview they lied. Each interview consisted of two phases. In Phase 1 they discussed their alleged opinion (truth…
Descriptors: Opinions, Accuracy, Deception, Credibility
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
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
Tang, Xiaowei; Shu, Gang; Wei, Bing; Levin, Daniel – Science Education, 2024
Students often learn about measurement uncertainty as an isolated topic, with a focus on generalizable strategies to manage uncertainty in scientific investigation. In this study, we report and analyze a case of emergent learning about measurement and uncertainty, in which students in a Chinese elementary school science class explored and…
Descriptors: Foreign Countries, Elementary School Students, Elementary School Science, Science Process Skills
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
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
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
Beechey, Timothy – Journal of Speech, Language, and Hearing Research, 2023
Purpose: This article provides a tutorial introduction to ordinal pattern analysis, a statistical analysis method designed to quantify the extent to which hypotheses of relative change across experimental conditions match observed data at the level of individuals. This method may be a useful addition to familiar parametric statistical methods…
Descriptors: Hypothesis Testing, Multivariate Analysis, Data Analysis, Statistical Inference
Alison G. Lynch; Elise Lockwood; Amy B. Ellis – Research in Mathematics Education, 2024
In this paper, we explore the role that examples play as mathematicians formulate conjectures, and we describe and exemplify one particular example-related activity that we observed in interviews with thirteen mathematicians. During our interviews, mathematicians productively used examples as they formulated conjectures, particularly by creating…
Descriptors: College Faculty, Mathematical Concepts, Mathematics Education, Mathematics Instruction
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
Musil, Libor; Jaklová Strihavková, Daniela – Journal of Social Work Education, 2020
The assumed impossibility of forming a widely accepted view of social work is explained on the one hand by the contesting nature of social work definitions and on the other by a loss of professional identity since the 1960s. The aim of the article is to elaborate a third explanation based on the hypothesis that social workers adhere to their…
Descriptors: Social Work, Definitions, Caseworkers, Hypothesis Testing
Masnick, Amy M.; Morris, Bradley J. – Education Sciences, 2022
Data reasoning is an essential component of scientific reasoning, as a component of evidence evaluation. In this paper, we outline a model of scientific data reasoning that describes how data sensemaking underlies data reasoning. Data sensemaking, a relatively automatic process rooted in perceptual mechanisms that summarize large quantities of…
Descriptors: Models, Science Process Skills, Data Interpretation, Cognitive Processes
Sun-Joo Cho; Amanda Goodwin; Matthew Naveiras; Paul De Boeck – Journal of Educational Measurement, 2024
Explanatory item response models (EIRMs) have been applied to investigate the effects of person covariates, item covariates, and their interactions in the fields of reading education and psycholinguistics. In practice, it is often assumed that the relationships between the covariates and the logit transformation of item response probability are…
Descriptors: Item Response Theory, Test Items, Models, Maximum Likelihood Statistics
Joshi, Megha; Pustejovsky, James E.; Beretvas, S. Natasha – Research Synthesis Methods, 2022
The most common and well-known meta-regression models work under the assumption that there is only one effect size estimate per study and that the estimates are independent. However, meta-analytic reviews of social science research often include multiple effect size estimates per primary study, leading to dependence in the estimates. Some…
Descriptors: Meta Analysis, Regression (Statistics), Models, Effect Size