Evaluating the median p-value method for assessing the statistical significance of tests when using multiple imputation
Austin PC, Eekhout I, van Buuren S. J Appl Stat. 2025; 52(6):1161-1176. Epub 2024; Oct 25.
Objective — To describe agreement between administrative and self-report data on the number and type of chronic conditions (CCs) and determine whether associations between CC count and health service use differ by data source.
Study Design and Setting — We linked Canadian Community Health Survey and administrative data for a cohort of adults aged 45+ in Ontario and identified 12 CCs from both data sources. Agreement was described by count and constituent CCs. We estimated associations between CC count (self-report and administrative data) and health service use (administrative data only) over one year.
Results — Among 71,317 adults, 26.9% showed agreement on both count and constituent CCs but agreement declined with increasing CCs. Health service use increased with CC count but the association was stronger when CCs were measured with administrative data. For example, when measured with administrative data, the odds of a general practitioner visit for 5+ CCs vs none was 20.3 (95%CI 20.0-20.5) but when using self-report data, the estimate was 8.0 (95% CI 7.8-8.2).
Conclusion — Agreement on the number of CCs was low and resulted in different estimates on the association with health service use, illustrating the challenges in CC measurement and the ability to interpret the effects on outcomes.
Gruneir A, Griffith LE, Fisher K, Perez R, Favotto L, Patterson C, Markle-Reid M, Ploeg J, Upshur R. J Clin Epidemiol. 2020; 124:173-82. Epub 2020 Apr 27.
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