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Ben Kelcey; Fangxing Bai; Amota Ataneka; Yanli Xie; Kyle Cox – Society for Research on Educational Effectiveness, 2024
We consider a class of multiple-group individually-randomized group trials (IRGTs) that introduces a (partially) cross-classified structure in the treatment condition (only). The novel feature of this design is that the nature of the treatment induces a clustering structure that involves two or more non-nested groups among individuals in the…
Descriptors: Randomized Controlled Trials, Research Design, Statistical Analysis, Error of Measurement
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Andrew Jaciw – Society for Research on Educational Effectiveness, 2024
Background: Rooted in problems of social justice, intersectionality addresses intragroup differences in impacts and outcomes and the compound discrimination at specific intersections of classification (Crenshaw,1991). It stresses that deficits/debts in outcomes often occur non-additively; for example, discriminatory hiring practices can be…
Descriptors: Intersectionality, Classification, Randomized Controlled Trials, Factor Analysis
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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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David Broska; Michael Howes; Austin van Loon – Sociological Methods & Research, 2025
Large language models (LLMs) provide cost-effective but possibly inaccurate predictions of human behavior. Despite growing evidence that predicted and observed behavior are often not "interchangeable," there is limited guidance on using LLMs to obtain valid estimates of causal effects and other parameters. We argue that LLM predictions…
Descriptors: Artificial Intelligence, Observation, Prediction, Correlation
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Sourabh Balgi; Adel Daoud; Jose M. Peña; Geoffrey T. Wodtke; Jesse Zhou – Sociological Methods & Research, 2025
Social science theories often postulate systems of causal relationships among variables, which are commonly represented using directed acyclic graphs (DAGs). As non-parametric causal models, DAGs require no assumptions about the functional form of the hypothesized relationships. Nevertheless, to simplify empirical evaluation, researchers typically…
Descriptors: Graphs, Causal Models, Statistical Inference, Artificial Intelligence
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Amy Shelton; Collin Hitt – Journal of School Choice, 2024
There are over one million school-age children in Missouri, and we estimate 61,000 (6% of all school-age children) are homeschooled. Missouri is one of 29 states that does not require homeschooling to be reported. Using methods that can be replicated elsewhere with publicly available data, we test three approaches to estimating homeschool…
Descriptors: Home Schooling, Attendance, Data Collection, School Statistics
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Xiao Liu; Zhiyong Zhang; Kristin Valentino; Lijuan Wang – Grantee Submission, 2024
Parallel process latent growth curve mediation models (PP-LGCMMs) are frequently used to longitudinally investigate the mediation effects of treatment on the level and change of outcome through the level and change of mediator. An important but often violated assumption in empirical PP-LGCMM analysis is the absence of omitted confounders of the…
Descriptors: Mediation Theory, Bayesian Statistics, Growth Models, Monte Carlo Methods
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Xiao Liu; Zhiyong Zhang; Kristin Valentino; Lijuan Wang – Structural Equation Modeling: A Multidisciplinary Journal, 2024
Parallel process latent growth curve mediation models (PP-LGCMMs) are frequently used to longitudinally investigate the mediation effects of treatment on the level and change of outcome through the level and change of mediator. An important but often violated assumption in empirical PP-LGCMM analysis is the absence of omitted confounders of the…
Descriptors: Mediation Theory, Bayesian Statistics, Growth Models, Monte Carlo Methods
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Michael Schultz – Sociological Methods & Research, 2024
This paper presents a model of recurrent multinomial sequences. Though there exists a quite considerable literature on modeling autocorrelation in numerical data and sequences of categorical outcomes, there is currently no systematic method of modeling patterns of recurrence in categorical sequences. This paper develops a means of discovering…
Descriptors: Research Methodology, Sequential Approach, Models, Markov Processes
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Fangxing Bai; Ben Kelcey; Amota Ataneka; Yanli Xie; Kyle Cox; Nianbo Dong – Society for Research on Educational Effectiveness, 2024
Purpose: Multisite mediation studies are a cornerstone in mapping out developmental processes because they probe the mechanisms of a treatment while creating key opportunities to learn from and about variation in those mechanisms across sites. Despite the prevalence of multisite studies, a significant gap in the literature is how to plan such…
Descriptors: Randomized Controlled Trials, Mediation Theory, Statistical Analysis, Robustness (Statistics)
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Wendy Chan – Asia Pacific Education Review, 2024
As evidence from evaluation and experimental studies continue to influence decision and policymaking, applied researchers and practitioners require tools to derive valid and credible inferences. Over the past several decades, research in causal inference has progressed with the development and application of propensity scores. Since their…
Descriptors: Probability, Scores, Causal Models, Statistical Inference
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Yi, Zhiyao; Chen, Yi-Hsin; Yin, Yue; Cheng, Ke; Wang, Yan; Nguyen, Diep; Pham, Thanh; Kim, EunSook – Journal of Experimental Education, 2022
A simulation study was conducted to examine the efficacy of nine frequently-used HOV tests, including Levene's tests with squared residuals and with absolute residuals, Brown and Forsythe (BF) test, Bootstrap BF test, O'Brien test, Z-variance test, Box-Scheffé (BS) test, Bartlett test, and Pseudo jackknife test under comprehensive simulation…
Descriptors: Statistical Analysis, Robustness (Statistics), Sampling, Statistical Inference
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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
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Julian Schuessler; Peter Selb – Sociological Methods & Research, 2025
Directed acyclic graphs (DAGs) are now a popular tool to inform causal inferences. We discuss how DAGs can also be used to encode theoretical assumptions about nonprobability samples and survey nonresponse and to determine whether population quantities including conditional distributions and regressions can be identified. We describe sources of…
Descriptors: Data Collection, Graphs, Error of Measurement, Statistical Bias
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David Kaplan; Kjorte Harra – Large-scale Assessments in Education, 2024
This paper aims to showcase the value of implementing a Bayesian framework to analyze and report results from international large-scale assessments and provide guidance to users who want to analyse ILSA data using this approach. The motivation for this paper stems from the recognition that Bayesian statistical inference is fast becoming a popular…
Descriptors: Bayesian Statistics, Administrator Surveys, Teacher Surveys, Measurement
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