Literaturnachweis - Detailanzeige
| Autor/inn/en | Ames, Allison; Myers, Aaron |
|---|---|
| Titel | Digital Module 06: Bayesian Psychometrics-Posterior Predictive Model Checking https://ncme.elevate.commpartners.com |
| Quelle | In: Educational Measurement: Issues and Practice, 38 (2019) 2, S.116-117 (2 Seiten)Infoseite zur Zeitschrift
PDF als Volltext |
| Sprache | englisch |
| Dokumenttyp | gedruckt; online; Zeitschriftenaufsatz |
| ISSN | 0731-1745 |
| DOI | 10.1111/emip.12263 |
| Schlagwörter | Bayesian Statistics; Psychometrics; Models; Predictive Measurement; Goodness of Fit; Computation; Regression (Statistics); Item Response Theory; Data Interpretation; Coding; Diagnostic Tests; Learning Activities; Educational Resources; Glossaries; Statistical Inference |
| Abstract | Drawing valid inferences from modern measurement models is contingent upon a good fit of the data to the model. Violations of model-data fit have numerous consequences, limiting the usefulness and applicability of the model. As Bayesian estimation is becoming more common, understanding the Bayesian approaches for evaluating model-data fit models is critical. In this instructional module, Allison Ames and Aaron Myers provide an overview of Posterior Predictive Model Checking (PPMC), the most common Bayesian model-data fit approach. Specifically, they review the conceptual foundation of Bayesian inference as well as PPMC and walk through the computational steps of PPMC using real-life data examples from simple linear regression and item response theory analysis. They provide guidance for how to interpret PPMC results and discuss how to implement PPMC for other model(s) and data. The digital module contains sample data, SAS code, diagnostic quiz questions, data-based activities, curated resources, and a glossary. (As Provided). |
| Anmerkungen | Wiley-Blackwell. 350 Main Street, Malden, MA 02148. Tel: 800-835-6770; Tel: 781-388-8598; Fax: 781-388-8232; e-mail: cs-journals@wiley.com; Web site: http://www.wiley.com/WileyCDA |
| Erfasst von | ERIC (Education Resources Information Center), Washington, DC |
| Update | 2020/1/01 |
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