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Maxi Schulz; Malte Kramer; Oliver Kuss; Tim Mathes – Research Synthesis Methods, 2024
In sparse data meta-analyses (with few trials or zero events), conventional methods may distort results. Although better-performing one-stage methods have become available in recent years, their implementation remains limited in practice. This study examines the impact of using conventional methods compared to one-stage models by re-analysing…
Descriptors: Meta Analysis, Data Analysis, Research Methodology, Research Problems
Adam C. Sales; Ethan Prihar; Johann Gagnon-Bartsch; Ashish Gurung; Neil T. Heffernan – Grantee Submission, 2022
Randomized A/B tests allow causal estimation without confounding but are often under-powered. This paper uses a new dataset, including over 250 randomized comparisons conducted in an online learning platform, to illustrate a method combining data from A/B tests with log data from users who were not in the experiment. Inference remains exact and…
Descriptors: Research Methodology, Educational Experiments, Causal Models, Computation
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Ben Van Dusen; Heidi Cian; Jayson Nissen; Lucy Arellano; Adrienne D. Woods – Sociology of Education, 2024
This investigation examines the efficacy of multilevel analysis of individual heterogeneity and discriminatory accuracy (MAIHDA) over fixed-effects models when performing intersectional studies. The research questions are as follows: (1) What are typical strata representation rates and outcomes on physics research-based assessments? (2) To what…
Descriptors: Educational Research, Intersectionality, Critical Race Theory, STEM Education
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Poschmann, Philipp; Goldenstein, Jan – Sociological Methods & Research, 2022
Despite the recent and ongoing progress in using text-mining tools to automatically analyze large text corpora, there remains significant potential to facilitate the study of social action in social science research. In this context, particularly the disambiguation (who is referred to in a text?) and specification (which demographic…
Descriptors: Web Sites, Collaborative Writing, Reliability, Accuracy
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Nokelainen, Petri; Silander, Tomi – Frontline Learning Research, 2014
This commentary to the recent article by Musso et al. (2013) discusses issues related to model fitting, comparison of classification accuracy of generative and discriminative models, and two (or more) cultures of data modeling. We start by questioning the extremely high classification accuracy with an empirical data from a complex domain. There is…
Descriptors: Models, Classification, Accuracy, Regression (Statistics)
Makel, Matthew C., Ed.; Plucker, Jonathan A., Ed. – APA Books, 2017
The promise of science is that its methods cause others to believe its results. This foundation is served by trust, accuracy, and transparency. Unfortunately, current research practices in psychology are known to often produce inaccurate, irreproducible, and imprecise results. "Toward a More Perfect Psychology" introduces a plethora of…
Descriptors: Psychology, Research Methodology, Trust (Psychology), Accuracy
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Shortridge, Ashton; Goldsberry, Kirk; Weessies, Kathleen – Journal of Geography, 2011
This article characterizes and measures errors in the 2010 National Research Council (NRC) assessment of research-doctorate programs in geography. This article provides a conceptual model for data-based sources of uncertainty and reports on a quantitative assessment of NRC research data uncertainty for a particular geography doctoral program.…
Descriptors: Geography, Doctoral Programs, Graduate Study, Educational Assessment