Journal article
STRATIFIED TESTS, STRATIFIED SLOPES, AND RANDOM EFFECTS MODELS FOR CLINICAL TRIALS WITH MISSING DATA
Journal of biopharmaceutical statistics, Vol.10(4), pp.447-455
11/22/2000
DOI: 10.1081/BIP-100101977
PMID: 11104386
Abstract
Because missing observations may affect the size and power of statistical tests of equality, various analytical techniques explicitly or implicitly condition the analysis on the amount of information available per person. We illustrate the difference between stratifying a slope estimate and stratifying a test statistic based on slopes. We compare a nonparametric version of the latter approach with the parametric tests available from SAS Proc Mixed. Power and size of these two approaches are considered under different parametric settings, distributions, and missing data mechanisms.
Details
- Title: Subtitle
- STRATIFIED TESTS, STRATIFIED SLOPES, AND RANDOM EFFECTS MODELS FOR CLINICAL TRIALS WITH MISSING DATA
- Creators
- Jeffrey D Dawson - Department of Biostatistics , University of IowaSeung-Ho Han - Department of Pediatrics , University of Iowa
- Resource Type
- Journal article
- Publication Details
- Journal of biopharmaceutical statistics, Vol.10(4), pp.447-455
- DOI
- 10.1081/BIP-100101977
- PMID
- 11104386
- NLM abbreviation
- J Biopharm Stat
- ISSN
- 1054-3406
- eISSN
- 1520-5711
- Publisher
- Taylor & Francis Group
- Language
- English
- Date published
- 11/22/2000
- Academic Unit
- Public Health Administration; Biostatistics
- Record Identifier
- 9983997464302771
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