UM Logo

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

Material type: TextTextPublisher: New York, NY : Routledge, ©2020Description: vi, 284 pages: illustrations; 23 cmContent type:
  • text
Media type:
  • computer
Carrier type:
  • online resource
ISBN:
  • 9780429273872
Subject(s): Additional physical formats: Print version:: Small sample size solutions : a guide for applied researchers and practitioners.DDC classification:
  • 2020 DC 001.42 Sm181
LOC classification:
  • Q180.55.M4
Online resources:
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
Tags from this library: No tags from this library for this title. Log in to add tags.
Star ratings
    Average rating: 0.0 (0 votes)
Holdings
Item type Current library Collection Call number Status Date due Barcode
Circulation Circulation UM Digos College - LIC Circulation DC 001.42 Sm181 2020 (Browse shelf(Opens below)) Available 26425

Includes index.

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

Unrestricted online access

Description based on online resource; title from PDF title page (viewed on 06/25/2020)

There are no comments on this title.

to post a comment.