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Small sample size solutions : a guide for applied researchers and practitioners

Small sample size solutions : a guide for applied researchers and practitioners

자료유형
단행본
개인저자
Schoot, Rens van de. Miočevic, Milica.
서명 / 저자사항
Small sample size solutions : a guide for applied researchers and practitioners / edited by Rens van de Schoot and Milica Miočevic.
발행사항
Abingdon, Oxon :   Routledge,   2020.  
형태사항
xiv, 269 p. : ill. (chiefly col.) ; 24 cm.
총서사항
European association of methodology series
ISBN
9780367221898 (hbk.) 9780367222222 (pbk.)
서지주기
Includes bibliographical references and index.
일반주제명
Research --Methodology. Data sets.
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300 ▼a xiv, 269 p. : ▼b ill. (chiefly col.) ; ▼c 24 cm.
490 1 ▼a European association of methodology series
504 ▼a Includes bibliographical references and index.
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소장정보

No. 소장처 청구기호 등록번호 도서상태 반납예정일 예약 서비스
No. 1 소장처 중앙도서관/서고6층/ 청구기호 001.42 S635 등록번호 111846790 도서상태 대출가능 반납예정일 예약 서비스 B M

컨텐츠정보

목차

ntroduction (Van de Schoot and Miocevic)


List of Symbols





Part I: Bayesian solutions


1. Introduction to Bayesian statistics (Miocevic, 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 (Miocevic, 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 (Veen and Egberts)


5. A tutorial on Bayesian penalized regression with shrinkage priors for small sample sizes (van Erp)





Part II: n=1


6. One by one: the design and analysis of replicated randomized single-case experiments (Onghena)


7. Single-case experimental designs in clinical intervention research (Maric and van der Werff)


8. How to improve the estimation of a specific examinee''s (n=1) math ability when test data are limited (Lek and Arts)


9. Combining evidence over multiple individual analyses (Klaassen)


10. Going multivariate in clinical trial studies: a Bayesian framework for multiple binary outcomes (Kavelaars)





Part III: Complex hypotheses and models


11. An introduction to restriktor: evaluating informative hypotheses for linear models (Vanbrabant and Rosseel)


12. Testing replication with small samples: applications to ANOVA (Zondervan-Zwijnenburg and 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 (Hox and 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 (Smid and Rosseel)


18. Important yet unheeded: some small sample issues that are often overlooked (Hox)


Index

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