Constructing a T‐Test for Value Function Comparison of Individualized Treatment Regimes in the Presence of Multiple Imputation for Missing Data
Year: 2025
Type: article
Abstract: Optimal individualized treatment decision-making has improved health outcomes in recent years. The value function is commonly used to evaluate the goodness of an individualized treatment decision rule. Despite recent advances, comparing value functions between different treatment decision rules or constructing confidence intervals around value functions remains difficult. We propose a t-test based method applied to a test set that generates valid p-values to compare value functions between a given pair of treatment decision rules when some of the data are missing. We demonstrate the ease in use of this method and evaluate its performance via simulation studies and apply it to the China Health and Nutrition Survey data.
Source: UNC Libraries
DOI: 10.17615/2rnw-m855
Institution: University of North Carolina at Chapel Hill
Language: English
Subfield: Statistics and Probability
Field: Mathematics
Domain: Physical Sciences
Open Access status: green
Funders: Chinese Center for Disease Control and Prevention, National Health and Family Planning Commission of the People's Republic of China, Centers for Disease Control and Prevention, National Institute on Aging, National Heart, Lung, and Blood Institute, Fogarty International Center, National Institute of Diabetes and Digestive and Kidney Diseases, National Center for Advancing Translational Sciences, Eunice Kennedy Shriver National Institute of Child Health and Human Development
OpenAlex ID: W7202039596