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Evaluating public health interventions: 3. the two-stage design for confounding bias reduction-having your cake and eating it two

D. Spiegelman, C.L. Rivera-Rodriguez and S. Haneuse

American Journal of Public Health, 2016, vol. 106, issue 7, 1223-1226

Abstract: In public health evaluations, confounding bias in the estimate of the intervention effect will typically threaten the validity of the findings. It is a common misperception that the only way to avoid this bias is to measure detailed, high-quality data on potential confounders for every intervention participant, but this strategy for adjusting for confounding bias is often infeasible. Rather than ignoring confounding altogether, the twophase design and analysis-in which detailed high-quality confounding data are obtained among a small subsample-can be considered. We describe the two-stage design and analysis approach, and illustrate its use in the evaluation of an intervention conducted in Dar es Salaam, Tanzania, of an enhanced community health worker program to improve antenatal care uptake.

Keywords: eating; health auxiliary; human; human experiment; prenatal care; Tanzania; epidemiology; health auxiliary; maternal welfare; measurement accuracy; methodology; organization and management; public health; reproducibility; socioeconomics; standards, Community Health Workers; Confounding Factors (Epidemiology); Data Accuracy; Humans; Maternal Health; Prenatal Care; Public Health; Reproducibility of Results; Research Design; Socioeconomic Factors; Tanzania (search for similar items in EconPapers)
Date: 2016
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http://hdl.handle.net/10.2105/AJPH.2016.303250

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Persistent link: https://EconPapers.repec.org/RePEc:aph:ajpbhl:10.2105/ajph.2016.303250_3

DOI: 10.2105/AJPH.2016.303250

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