Linked Life Data

9699236

Source:http://linkedlifedata.com/resource/pubmed/id/9699236

Statements in which the resource exists as a subject.
PredicateObject
rdf:type
lifeskim:mentions
pubmed:issue
14
pubmed:dateCreated
1998-11-12
pubmed:abstractText
Derivation of the minimum sample size is an important consideration in an applied research effort. When the outcome is measured at a single time point, sample size procedures are well known and widely applied. The corresponding situation for longitudinal designs, however, is less well developed. In this paper, we adapt the generalized estimating equation (GEE) approach of Liang and Zeger to sample size calculations for discrete and continuous outcome variables. The non-central version of the Wald Chi 2 test is considered. We use the damped exponential family of correlation structures described in Muñoz et al. for the 'working' correlation matrix among the repeated measures. We present a table of minimum sample sizes for binary outcomes, and discuss extensions that account for unequal allocation, staggered entry and loss to follow-up.
pubmed:grant
pubmed:language
eng
pubmed:journal
pubmed:citationSubset
IM
pubmed:status
MEDLINE
pubmed:month
Jul
pubmed:issn
0277-6715
pubmed:author
pubmed:issnType
Print
pubmed:day
30
pubmed:volume
17
pubmed:owner
NLM
pubmed:authorsComplete
Y
pubmed:pagination
1643-58
pubmed:dateRevised
2007-11-15
pubmed:meshHeading
pubmed:year
1998
pubmed:articleTitle
Application of GEE procedures for sample size calculations in repeated measures experiments.
pubmed:affiliation
Biostatistics Center, George Washington University, Rockville, MD 20852, USA. rochon@biostat.bsc.gwu.edu
pubmed:publicationType
Journal Article, Research Support, U.S. Gov't, P.H.S.