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A single variable analysis was performed.
Of interest in this continuous variable analysis was that risk for worsening of eGFR was significant with baseline PP (HR 1.01, P = 0.03).
A multiple variable analysis was not performed due to the relatively low proportion of patients with any one exposure (and therefore limited statistical power) and the likelihood of co-linearity between exposures.
We did not use propensity scores as they suffer the same limitations from unmeasured confounding, while instrumental variable analysis was considered but rejected due to the absence of a suitable instrument.
Similar(56)
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.
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).
Variables with a p value <0.1 from the single-risk variable analysis were included initially.
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.
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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