Small sample size solutions a guide for applied researchers and practitioners / edited by Rens van de Schoot and Milica Mio cevic.

Format Electronic
Publication InfoAbingdon, Oxon ; New York, NY : Routledge, an imprint of the Taylor & Francis Group, an informa business, [2020]
Description1 online resource (284 pages)
Supplemental ContentFull text available from Taylor & Francis eBooks
Subjects

Contents Introduction (Van de Schootand Mio cevi c) List of Symbols Part I: Bayesian solutions 1. Introduction to Bayesian statistics(Mio cevi c, Levy,and van de Schoot) 2.The role of exchangeability in sequential updating of findings from small studies and the challenges of identifying exchangeable data sets (Mio cevi c, Levy,and Savord) 3. A tutorial on using the WAMBS checklist to avoid the misuse of Bayesian statistics(van de Schoot, Veen, Smeets, Winter,and Depaoli) 4. The importance of collaboration in Bayesian analyses with small samples (Veenand Egberts) 5. A tutorial on Bayesian penalized regression with shrinkage priors for small sample sizes (van Erp) PartII: n=1 6. One by one: the designand analysis of replicated randomized single-case experiments(Onghena) 7. Single-case experimental designs in clinical intervention research (Maricand van der Werff) 8. How to improve the estimation of a specific examinee's (n=1)math ability when test data are limited(Lekand Arts) 9. Combining evidence over multiple individual analyses(Klaassen) 10. Going multivariate in clinical trial studies: a Bayesian framework for multiple binary outcomes(Kavelaars) PartIII: Complex hypotheses and models 11. An introduction to restriktor: evaluating informative hypotheses for linear models (VanbrabantandRosseel) 12. Testing replication with small samples: applications to ANOVA(Zondervan-Zwijnenburgand Rijshouwer) 13. Small sample meta-analyses: exploring heterogeneity using MetaForest (van Lissa) 14. Item parcels as indicators: why, when, and how to use them in small sample research(Rioux, Stickley, Odejimi,and Little) 15. Small samples in multilevel modeling(Hoxand McNeish) 16. Small sample solutions for structural equation modeling(Rosseel) 17. SEM with small samples: two-step modeling and factor score regression versus Bayesian estimation with informative priors (Smidand Rosseel) 18. Important yet unheeded: some small sample issues that are often overlooked(Hox) Index
Bibliography noteIncludes bibliographical references and index.
Access restrictionAvailable only to authorized users.
Technical detailsMode of access: World Wide Web
Terms of useCreative Commons Attribution-NonCommercial-NoDerivatives 4.0 International CC BY-NC-ND https://creativecommons.org/licenses/by-nc-nd/4.0/legalcode
Source of descriptionDescription based on online resource; title from PDF title page (viewed on 06/25/2020)
Issued in other formPrint version: Small sample size solutions : a guide for applied researchers and practitioners. Abingdon, Oxon ; New York, NY : Routledge, an imprint of the Taylor & Francis Group, an informa business, [2020] 9780367221898 9780367222222
Genre/formElectronic books.
LCCN 2020394788
ISBN9780429273872 (pdf)
ISBN(hc)
ISBN(pb)

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