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- W2017577291 abstract "Abstract Although omitting covariates associated with the response in generalized linear models can yield seriously biased estimates of the effects of the included covariates, in certain settings there is no bias. This article considers the effect of omitted covariates on the efficiency of the estimated effects of the included covariates in these cases. I consider the case where the omitted covariate is independent of the included covariates, as in studies with randomized treatment assignment, as well as the case where the omitted covariate is correlated with the included but not a confounder. I present expressions to show that omitting covariates associated with the response and independent of the included covariate can result in serious efficiency losses for estimates of the effects of the included covariates. I also present expressions to show that omitting nonconfounding covariates can lead to efficiency gains. These expressions also quantify the magnitude of estimation efficiency with omitted covaria..." @default.
- W2017577291 created "2016-06-24" @default.
- W2017577291 creator A5007432044 @default.
- W2017577291 date "1998-09-01" @default.
- W2017577291 modified "2023-09-25" @default.
- W2017577291 title "Estimation Efficiency With Omitted Covariates in Generalized Linear Models" @default.
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- W2017577291 doi "https://doi.org/10.1080/01621459.1998.10473773" @default.
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