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Year : 2019  |  Volume : 2  |  Issue : 1  |  Page : 48-50

Survey research methods: A guide for creating post-stratification weights to correct for sample bias

Department of Clinical Sciences, North Carolina State University, Raleigh, North Carolina, USA

Correspondence Address:
Dr. Kenneth D Royal
Department of Clinical Sciences, College of Veterinary Medicine, North Carolina State University, Raleigh, North Carolina
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Source of Support: None, Conflict of Interest: None

DOI: 10.4103/EHP.EHP_8_19

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Nonrepresentative data pose one of the greatest validity threats in survey research. Samples that are underrepresented and/or overrepresented based on demographic subgroups can introduce bias that distorts both the accuracy and the inferences made about the results. This article discusses the concept of poststratification weighting, a post hoc statistical procedure used to correct for sampling bias in survey research studies. Procedural steps for calculating poststratification weights are presented, and an example involving a simulated cohort of students in a medical school is provided for demonstration purposes. SPSS statistical software coding is presented to help researchers get started with their own calculations of poststratification weights.

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