Abstract
Objective
The estimation of the number needed to be exposed (NNE) with adjustment for covariates
can be performed by inverting the corresponding adjusted risk difference. The latter
can be estimated by several approaches based on binomial and Poisson regression with
or without constraints. A novel proposal is given by logistic regression with average
risk difference (LR-ARD) estimation. Finally, the use of ordinary linear regression
and unadjusted estimation can be considered.
Study Design and Setting
LR-ARD is compared with alternative approaches regarding bias, precision, and coverage
probability by means of an extensive simulation study.
Results
LR-ARD was found to be superior compared with the other approaches. In the case of
balanced covariates and large sample sizes, unadjusted estimation and ordinary linear
regression can also be used. In general, however, LR-ARD seems to be the most appropriate
approach to estimate adjusted risk differences and NNEs.
Conclusions
To estimate risk differences and NNEs with adjustment for covariates, the LR-ARD approach
should be used.
Keywords
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Article info
Publication history
Published online: April 30, 2010
Accepted:
January 22,
2010
Identification
Copyright
© 2010 Elsevier Inc. Published by Elsevier Inc. All rights reserved.
