Remark AS R51: A Remark on AS 162. Multivariate Conditional Logistic Analysis of Stratum-Matched Case-Control Studies

1984 ◽  
Vol 33 (1) ◽  
pp. 123
Author(s):  
Mark D. Krailo
Keyword(s):  
Case Control ◽  
Case Control Studies ◽  
Logistic Analysis ◽  
Matched Case

Evaluation of Exact and Asymptotic Interval Estimators in Logistic Analysis of Matched Case-Control Studies

Biometrics ◽  
1991 ◽  
Vol 47 (4) ◽  
pp. 1311 ◽  
Author(s):  
Stein E. Vollset ◽  
Karim F. Hirji ◽  
Abdelmonem A. Afifi
Keyword(s):  
Case Control ◽  
Case Control Studies ◽  
Logistic Analysis ◽  
Matched Case ◽  
Interval Estimators

scholarly journals Role of Matching in Case-Control Studies of Antimicrobial Resistance

2009 ◽  
Vol 30 (5) ◽  
pp. 480-483 ◽  
Author(s):  
Elizabeth Cerceo ◽  
Ebbing Lautenbach ◽  
Darren R. Linkin ◽  
Warren B. Bilker ◽  
Ingi Lee
Keyword(s):  
Antimicrobial Resistance ◽  
Case Control ◽  
Case Control Studies ◽  
Matched Case

Of 57 case-control studies of antimicrobial resistance, matching was used in 23 (40%). Matched variables differed substantially across studies. Of these 23 matched case-control studies, 12 (52%) justified the use of matching, and 9 (39%) noted the strengths or limitations of this approach. Analysis that accounted for matching was performed in only 52% of the case-control studies.

scholarly journals Power and sample size for multivariate logistic modeling of unmatched case-control studies

2017 ◽  
Vol 28 (3) ◽  
pp. 822-834
Author(s):  
Mitchell H Gail ◽  
Sebastien Haneuse
Keyword(s):  
Logistic Regression ◽  
Sample Size ◽  
Case Control ◽  
Simulation Methods ◽  
Case Control Studies ◽  
Control Data ◽  
Logistic Analysis ◽  
Sample Size Calculations ◽  
Control Designs ◽  
Univariate Analyses

Sample size calculations are needed to design and assess the feasibility of case-control studies. Although such calculations are readily available for simple case-control designs and univariate analyses, there is limited theory and software for multivariate unconditional logistic analysis of case-control data. Here we outline the theory needed to detect scalar exposure effects or scalar interactions while controlling for other covariates in logistic regression. Both analytical and simulation methods are presented, together with links to the corresponding software.

Tests of Effect in 1: J Matched Case-Control Studies Based on a Modified Likelihood Approach

Biometrika ◽  
1990 ◽  
Vol 77 (4) ◽  
pp. 897
Author(s):  
Bryan Langholz ◽  
Duncan Thomas ◽  
Tsunjen Chen ◽  
Phillip Rhodes
Keyword(s):  
Case Control ◽  
Case Control Studies ◽  
Matched Case ◽  
Likelihood Approach ◽  
Modified Likelihood
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