2022 JUL 19 (NewsRx) — By a News Reporter-Staff News Editor at Insurance Daily News — Investigators discuss new findings in Managed Care. According to news reporting out of Madison, Wisconsin, by NewsRx editors, research stated, “There is an increasing interest in estimating heterogeneity in causal effects in randomized and observational studies. However, little research has been conducted to understand effect heterogeneity in an instrumental variables study.”
Funders for this research include National Institutes of Health (NIH) – USA, National Science Foundation (NSF).
Our news journalists obtained a quote from the research from the University of Wisconsin Madison, “In this work we present a method to estimate heterogeneous causal effects using an instrumental variable with matching. The method has two parts. The first part uses subject-matter knowledge and interpretable machine-learning techniques, such as classification and regression trees, to discover potential effect modifiers. The second part uses closed testing to test for statistical significance of each effect modifier while strongly controlling the familywise error rate. We apply this method on the Oregon Health Insurance Experiment, estimating the effect of Medicaid on the number of days an individual’s health does not impede their usual activities by using a randomized lottery as an instrument.”
According to the news editors, the research concluded: “Our method revealed Medicaid’s effect was most impactful among older, English-speaking, non-Asian males and younger, English-speaking individuals with, at most, a high school diploma or General Educational Development.”
This research has been peer-reviewed.
For more information on this research see: Detecting Heterogeneous Treatment Effects With Instrumental Variables and Application To the Oregon Health Insurance Experiment. Annals of Applied Statistics, 2022;16(2):1111-1129. Annals of Applied Statistics can be contacted at: Inst Mathematical Statistics-ims, 3163 Somerset Dr, Cleveland, OH 44122, USA.
Our news journalists report that additional information may be obtained by contacting Michael Johnson, University of Wisconsin Madison, Dept. of Statistics, Madison, WI 53706, United States. Additional authors for this research include Hyunseung Kang and Jiongyi Cao.
The direct object identifier (DOI) for that additional information is: https://doi.org/10.1214/21-AOAS1535. This DOI is a link to an online electronic document that is either free or for purchase, and can be your direct source for a journal article and its citation.
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