Does Home Health Care Increase the Probability of 30-Day Hospital Readmissions? Interpreting Coefficient Sign Reversals, or Their Absence, in Binary Logistic Regression Analysis

DOI10.1080/00031305.2019.1704873OpenAlexW2995495794MaRDI QIDQ5056964

Alecos Papadopoulos, Roland Stärk

Publication date: 14 December 2022

Published in: The American Statistician (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1080/00031305.2019.1704873

zbMATH Keywords

consistencycausalitytreatment effectignorabilitycontrol variables

Mathematics Subject Classification ID

Statistics (62-XX)

Cites Work

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• A further result on the sign of restricted least-squares estimates
• A result on the sign of restricted least-squares estimates
• On obtaining the right sign of a coefficient estimate by omitting a variable from the regression
• The central role of the propensity score in observational studies for causal effects
• Biased estimates of treatment effect in randomized experiments with nonlinear regressions and omitted covariates
• Some Surprising Results about Covariate Adjustment in Logistic Regression Models
• Reversals of Least-Square Estimates and Model-Invariant Estimation for Directions of Unique Effects