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Han L, Pisani MA, Araujo KL, et al. Use of Self-Matching to Control for Stable Patient Characteristics While Addressing Time-Varying Confounding on Treatment Effect: A Case Study of Older Intensive Care Patients. Int J Stat Med Res. 2016;5:8-16doi: 10.6000/1929-6029.2016.05.01.2.
Han, L., Pisani, M. A., Araujo, K. L., & Allore, H. G. (2016). Use of Self-Matching to Control for Stable Patient Characteristics While Addressing Time-Varying Confounding on Treatment Effect: A Case Study of Older Intensive Care Patients. International journal of statistics in medical research, 58-16. https://doi.org/10.6000/1929-6029.2016.05.01.2
Han, Ling, et al. "Use of Self-Matching to Control for Stable Patient Characteristics While Addressing Time-Varying Confounding on Treatment Effect: A Case Study of Older Intensive Care Patients." International journal of statistics in medical research vol. 5 (2016): 8-16. doi: https://doi.org/10.6000/1929-6029.2016.05.01.2
Han L, Pisani MA, Araujo KL, Allore HG. Use of Self-Matching to Control for Stable Patient Characteristics While Addressing Time-Varying Confounding on Treatment Effect: A Case Study of Older Intensive Care Patients. Int J Stat Med Res. 2016;5:8-16. doi: 10.6000/1929-6029.2016.05.01.2. Epub 2016 Jan 08. PMID: 27123153; PMCID: PMC4844076.
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Int J Stat Med Res. 2016;5:8-16. doi: 10.6000/1929-6029.2016.05.01.2. Epub 2016 Jan 08.

Use of Self-Matching to Control for Stable Patient Characteristics While Addressing Time-Varying Confounding on Treatment Effect: A Case Study of Older Intensive Care Patients.

International journal of statistics in medical research

Ling Han, M A Pisani, K L B Araujo, Heather G Allore

Affiliations

  1. Department of Internal Medicine, Program on Aging, Yale School of Medicine, New Haven, CT, USA.
  2. Department of Internal Medicine, Program on Aging, Yale School of Medicine, New Haven, CT, USA; Department of Internal Medicine, Section of Pulmonary, Critical Care and Sleep Medicine, Yale School of Medicine, New Haven, CT, USA.
  3. Department of Internal Medicine, Program on Aging, Yale School of Medicine, New Haven, CT, USA; Department of Biostatistics, Yale School of Public Health, New Haven, CT, USA.

PMID: 27123153 PMCID: PMC4844076 DOI: 10.6000/1929-6029.2016.05.01.2

Abstract

Exposure-crossover design offers a non-experimental option to control for stable baseline confounding through self-matching while examining causal effect of an exposure on an acute outcome. This study extends this approach to longitudinal data with repeated measures of exposure and outcome using data from a cohort of 340 older medical patients in an intensive care unit (ICU). The analytic sample included 92 patients who received ≥1 dose of haloperidol, an antipsychotic medication often used for patients with delirium. Exposure-crossover design was implemented by sampling the 3-day time segments prior (

Keywords: Exposure-crossover design; causal effects; confounding; generalized estimating equation; self-matching

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