Falsification Tests for Instrumental Variable Designs With an Application to Tendency to Operate. Issue 2 (February 2019)

• Record Type: Journal Article
• Authors: Keele, Luke; Zhao, Qingyuan; Kelz, Rachel R.; Small, Dylan
• Is Part Of: Medical care. Volume 57:Issue 2(2019)
• Publication Date: 2019-02
• Subjects: surgery -- instrumental variables -- falsification tests; Economics, Medical -- Periodicals; Insurance, Health -- Periodicals; Santé, Services de -- Administration -- Périodiques; Soins médicaux -- Périodiques; Medical economics -- Periodicals; Health insurance -- Periodicals; Medical economics -- United States -- Periodicals; Health insurance -- United States -- Periodicals; Comprehensive Health Care -- Periodicals; Personal Health Services -- Periodicals; Gezondheidszorg; Économie de la santé -- Périodiques; Santé, Services de -- Périodiques; Health insurance; Medical economics; United States; Periodicals; 362.10973
• DOI: 10.1097/MLR.0000000000001040
• Languages: English
• ISSNs: 0025-7079

Abstract

Abstract : Background: Instrumental variable (IV) methods are becoming an increasingly important tool in health services research as they can provide consistent estimates of causal effects in the presence of unobserved confounding. However, investigators must provide justifications that the IV is independent with any unmeasured confounder and its effect on the outcome occurs only through receipt of the exposure. These assumptions, while plausible in some contexts, cannot be verified from the data. Methods: Falsification tests can be applied to provide evidence for the key IV assumptions. A falsification test cannot prove the assumptions hold, but can provide decisive evidence when the assumption fails. We provide a general overview of falsification tests for IV designs. We highlight a falsification test that utilizes a subpopulation of the data where an overwhelming proportion of units are treated or untreated. If the IV assumptions hold, we should find the intention-to-treat effect is zero within these subpopulations. Results: We demonstrate the usage of falsification tests for IV designs using an IV known as tendency to operate from health services research. We show that the falsification test provides no evidence against the IV assumptions in this application.