A computer program to estimate power and relative efficiency to assess multiplicative interactions in flexibly matched case-control studies

2004 ◽  
Vol 74 (3) ◽  
pp. 261-265 ◽  
Author(s):  
T Stürmer ◽  
O Gefeller ◽  
H Brenner
Keyword(s):  
Computer Program ◽  
Relative Efficiency ◽  
Case Control ◽  
Case Control Studies ◽  
Matched Case

A Computer Program to Estimate Power and Relative Efficiency of Flexibly Matched Case-control Studies

2005 ◽  
Vol 44 (05) ◽  
pp. 693-696 ◽  
Author(s):  
O. Gefeller ◽  
H. Brenner ◽  
T. Stürmer
Keyword(s):  
Computer Program ◽  
Relative Efficiency ◽  
Odds Ratio ◽  
Null Hypothesis ◽  
Case Control ◽  
Case Control Studies ◽  
Test Statistic ◽  
Matched Case ◽  
Haenszel Test ◽  
Flexible Matching

Summary Objectives: We recently introduced the concept of flexible matching strategies with varying proportions of a dichotomous matching factor among controls to increase power and efficiency of case-control studies. We now present a method and a computer program to calculate power and relative efficiency compared to an unmatched design varying the proportion of the matching factor in controls over all possible values from 0 to 100 percent. Methods: For all these values, the program calculates the expected variance of the combined Mantel-Haenszel odds ratio and determines the power using the standard error of the expected combined Mantel-Haenszel odds ratio under the null hypothesis as derived from the Mantel-Haenszel test statistic without continuity correction. Results: Thereby, the program allows estimating the optimal prevalence of the matching factor in selected controls for a given scenario which often differs from the prevalence in cases. It furthermore allows to estimate loss in power and efficiency compared to optimal matching by suboptimal matching. Conclusions: Estimations like these are helpful with respect to the decision when to stop efforts to optimize the degree of matching during the recruitment of controls. Our program will strongly facilitate assessing the benefits of flexible matching strategies.

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.

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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