Do Missing Values Influence Outcomes in a Cross-sectional Mail Survey?

ABSTRACT:

Objective

To determine the effects of missing and inconsistent data on a weight management mail survey results.

Patients and methods

Weight management surveys were sent to 5000 overweight and obese individuals in the Learning Health System Network. Survey information was collected between October 27, 2017, and March 1, 2018. Some participants reported body mass index (BMI) values inconsistent with the intended overweight and obese sampling cohort. Analyses were performed after excluding these surveys and also performed again after setting these low BMI values to missing. Models were run after imputing missing values using expectation-maximization, Markov chain Monte Carlo, random forest imputation, multivariate imputation by chained equations, and multiple imputation and rep

SUBMITTER: Novotny PJ 

PROVIDER: S-EPMC7930870 | biostudies-literature | 2021 Feb

REPOSITORIES: biostudies-literature