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Observational studies

Confounding adjustment (ANCOVA)

Please note that known or assumed cause-effect relations are the basis on which confounding adjustments are made. While including a confounder in the model reduces bias, the inclusion of a mediator or collider can induce bias, see Shrier I, Platt RW. Reducing bias through directed acyclic graphs. BMC Med Res Methodol 2008;8:70. Describe how variables are measured and provide a rationale for the selection of potential confounders. However, even with performed adjustments, confounding can persist, an issue that should be addressed in the discussion. Sensitivity analyses can be useful for assessing residual confounding resulting from unmeasured and imperfectly measured variables.

Confounding adjustment (PS)

The propensity scores have been calculated using a statistical model with several variables. Please describe how these variables are measured and provide a rationale for their selection. Please clarify also if any of the variables could induce adjustment bias, see e.g. Sauer B, Brookhart MA, Roy JA, VanderWeele TJ. Developing a Protocol for Observational Comparative Effectiveness Research: A User’s Guide. Rockville (MD), Agency for Healthcare Research and Quality (US); 2013 Jan. Publication No.: 12(13)-EHC099. Chapter 7. Covariate Selection.

The Table 2 fallacy

Table 2 seems to reflect a case of the so-called Table 2 fallacy, see Westreich D, Greenland S. The table 2 fallacy: presenting and interpreting confounder and modifier coefficients. Am J Epidemiol 2013;177:292-298. Please describe the fitted models more clearly.

Primary endpoints

A primary outcome measure is presented. Structuring of endpoints into primary and secondary is usually part of a strategy for addressing multiplicity issues in randomised trials but is hardly relevant in an observational study as the one described here. Please clarify the terminology.

Stepwise regression

Statistical models are developed using stepwise regression, a method having precision (p-values) as selection criteria. It ignores cause-effect relations. However, while the inclusion of a confounder into a statistical model may reduce bias, the inclusion of a mediator or collider induces adjustent bias. If the purpose of the model is to provide clinically interpretable parameter estimates, stepwise regression is an inadequate method.

observ.txt · Last modified: 2020/03/04 10:53 by ranstam