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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
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Olanipekun, Oluwaseun L.; Zhao, JuLong; Wang, Rongdong; A. Sedory, Stephen; Singh, Sarjinder – Sociological Methods & Research, 2023
In carrying out surveys involving sensitive characteristics, randomized response models have been considered among the best techniques since they provide the maximum privacy protection to the respondents and procure honest responses. Over the years, researchers have carried out studies on the estimation of proportions of the population possessing…
Descriptors: Correlation, Smoking, Thinking Skills, Health Behavior
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Sami Mejri; Steven Borawski – International Journal on E-Learning, 2023
This article will address predictors of success for online students. A survey questionnaire was used to gather data concerning online students' social and educational readiness levels at a four-year private university in the Midwestern United States. Of the 4,050 potential participants, 250 (6.23%) responded to the survey. Stepwise regression…
Descriptors: Academic Persistence, Success, Online Courses, Readiness
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Yuan Hsiao; Lee Fiorio; Jonathan Wakefield; Emilio Zagheni – Sociological Methods & Research, 2024
Obtaining reliable and timely estimates of migration flows is critical for advancing the migration theory and guiding policy decisions, but it remains a challenge. Digital data provide granular information on time and space, but do not draw from representative samples of the population, leading to biased estimates. We propose a method for…
Descriptors: Migration, Migration Patterns, Data Collection, Data Analysis
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Grund, Simon; Lüdtke, Oliver; Robitzsch, Alexander – Journal of Educational and Behavioral Statistics, 2023
Multiple imputation (MI) is a popular method for handling missing data. In education research, it can be challenging to use MI because the data often have a clustered structure that need to be accommodated during MI. Although much research has considered applications of MI in hierarchical data, little is known about its use in cross-classified…
Descriptors: Educational Research, Data Analysis, Error of Measurement, Computation
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García-Murillo, Gabriel; Novoa-Hernández, Pavel; Rodri?uez, Rocío Serrano – Interactive Learning Environments, 2023
In this study, we report on a Systematic Mapping Study (SMS) for the application of technology acceptance models to Moodle under the prism of latent variable modeling. Based on an automatic search including primary studies from journals, conferences, and book chapters during 2001 to 2019, 41 primary were selected. We aim to contribute to a better…
Descriptors: Learning Management Systems, College Students, Technology Uses in Education, Educational Research
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Bloome, Deirdre; Schrage, Daniel – Sociological Methods & Research, 2021
Causal analyses typically focus on average treatment effects. Yet for substantive research on topics like inequality, interest extends to treatments' distributional consequences. When individuals differ in their responses to treatment, three types of inequality may result. Treatment may shape inequalities between subgroups defined by pretreatment…
Descriptors: Regression (Statistics), Outcomes of Treatment, Statistical Analysis, Correlation
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Tomek, Sara; Robinson, Cecil – Measurement: Interdisciplinary Research and Perspectives, 2021
Typical longitudinal growth models assume constant functional growth over time. However, there are often conditions where trajectories may not be constant over time. For example, trajectories of psychological behaviors may vary based on a participant's age, or conversely, participants may experience an intervention that causes trajectories to…
Descriptors: Growth Models, Statistical Analysis, Hierarchical Linear Modeling, Computation
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Huang, Ao; Komukai, Sho; Friede, Tim; Hattori, Satoshi – Research Synthesis Methods, 2021
Prospective registration of study protocols in clinical trial registries is a useful way to minimize the risk of publication bias in meta-analysis, and several clinical trial registries are available nowadays. However, they are mainly used as a tool for searching studies and information submitted to the registries has not been utilized as…
Descriptors: Publications, Bias, Meta Analysis, Selection
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Lyrica Lucas; Anum Khushal; Robert Mayes; Brian A. Couch; Joseph Dauer – International Journal of Science Education, 2025
Educational reform priorities such as emphasis on quantitative modelling (QM) have positioned undergraduate biology instructors as designers of QM experiences to engage students in authentic science practices that support the development of data-driven and evidence-based reasoning. Yet, little is known about how biology instructors adapt to the…
Descriptors: Undergraduate Students, College Science, Biology, Classroom Observation Techniques
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Kim, Jinho; Wilson, Mark – Educational and Psychological Measurement, 2020
This study investigates polytomous item explanatory item response theory models under the multivariate generalized linear mixed modeling framework, using the linear logistic test model approach. Building on the original ideas of the many-facet Rasch model and the linear partial credit model, a polytomous Rasch model is extended to the item…
Descriptors: Item Response Theory, Test Items, Models, Responses
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Goutte, Cyril; Durand, Guillaume – International Educational Data Mining Society, 2020
Learning curves are an important tool in cognitive diagnostics modeling to help assess how well students acquire new skills, and to refine and improve knowledge component models. Learning curves are typically obtained from a model estimated on real data obtained from a finite, and usually limited, sample of students. As a consequence, there is…
Descriptors: Learning, Models, Computation, Statistical Analysis
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Bouchet-Valat, Milan – Sociological Methods & Research, 2022
Notwithstanding a large body of literature on log-linear models and odds ratios, no general marginal-free index of the association in a contingency table has gained a wide acceptance. Building on a framework developed by L. A. Goodman, we put into light the direct links between odds ratios, the Altham index, the intrinsic association coefficient,…
Descriptors: Statistical Analysis, Tables (Data), Models, Foreign Countries
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Marek Arendarczyk; Tomasz J. Kozubowski; Anna K. Panorska – Journal of Statistics and Data Science Education, 2023
We provide tools for identification and exploration of data with very large variability having power law tails. Such data describe extreme features of processes such as fire losses, flood, drought, financial gain/loss, hurricanes, population of cities, among others. Prediction and quantification of extreme events are at the forefront of the…
Descriptors: Natural Disasters, Probability, Regression (Statistics), Statistical Analysis
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Nianbo Dong; Keith Herman; Benjamin Kelcey; Sirui Ren; Wendy Reinke; Jessaca Spybrook – Grantee Submission, 2025
Contextual, identity, and cultural factors are not only associated with student outcomes but can also serve to moderate the effects of interventions. However, the conventional analysis of moderation commonly used in school psychology is subject to the selection bias potentially introducing bias into estimated moderator effects. This article…
Descriptors: Causal Models, Statistical Analysis, Context Effect, Intervention
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