Inference following multiple imputation for generalized additive models: an investigation of the median p-value rule with applications to the Pulmonary Hypertension Association Registry and Colorado COVID-19 hospitalization data

Inference following multiple imputation for generalized additive models: an investigation of the median p-value rule with applications to the Pulmonary Hypertension Association Registry and Colorado COVID-19 hospitalization data

Abstract Background Missing data prove troublesome in data analysis; at best they reduce a study’s statistical power and at worst they induce bias in parameter estimates. Multiple imputation via chained equations is a popular technique for dealing with missing data. However, techniques for combining...

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Bibliographic Details
Main Authors: Matthew A. Bolt, Samantha MaWhinney, Jack W. Pattee, Kristine M. Erlandson, David B. Badesch, Ryan A. Peterson
Format: Article
Language:English
Published: BMC 2022-05-01
Series:BMC Medical Research Methodology
Subjects:
Missing data
Pooling results
Simulation study
Splines
Elevation
Pulmonary arterial hypertension
Online Access:https://doi.org/10.1186/s12874-022-01613-w

Internet

https://doi.org/10.1186/s12874-022-01613-w

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