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Instrumental variable analysis is an increasingly popular statistical method in epidemiologic research.
And perhaps more importantly, researchers will precisely describe situations when instrumental variable analysis is likely to be more biased.
Instrumental variable analysis is an econometric technique that allows causal inferences of the effectiveness of some treatments during situations to be made when a randomized trial has not been or cannot be conducted.
Although neither propensity score analysis nor instrumental variable analysis is perfect for a robust assessment, consistent results from instrumental variable analysis may serve as a useful confirmatory analysis for propensity score analyses.
The instrumental variable analysis is a novel aspect of the study design because the use of an effective instrument attempts to mimic a randomisation process and should result in the equal distribution of measured and unmeasured confounders among the different treatment groups.
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"The Public Health Impact of Antidepressants: An Instrumental Variable Analysis" was written by Mojtabai.
This example illustrates that features well described by the one-fast/two-slow variable analysis are not at all well described by a standard two-fast/one-slow variable analysis.
All analyses (except haplotype construction and instrumental variable analysis) were performed with SAS statistical software, version 9.1 (SAS Institute, Cary, USA).
A single variable analysis was performed.
Variables with a p value <0.1 from the single-risk variable analysis were included initially.
Variables with p-value of less than 0.15 in the single variable analysis were considered for selection in the multivariable analysis.
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