Skip to main page content
U.S. flag

An official website of the United States government

Dot gov

The .gov means it’s official.
Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

Https

The site is secure.
The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

Access keys NCBI Homepage MyNCBI Homepage Main Content Main Navigation
. 2013;7(4):2062-2080.
doi: 10.1214/13-AOAS665.

EVALUATING COSTS WITH UNMEASURED CONFOUNDING: A SENSITIVITY ANALYSIS FOR THE TREATMENT EFFECT

Elizabeth A Handorf  1 , Justin E Bekelman  2 , Daniel F Heitjan  2 , Nandita Mitra  2
Affiliations

EVALUATING COSTS WITH UNMEASURED CONFOUNDING: A SENSITIVITY ANALYSIS FOR THE TREATMENT EFFECT

Elizabeth A Handorf et al. Ann Appl Stat. 2013.

Abstract

Estimates of the effects of treatment on cost from observational studies are subject to bias if there are unmeasured confounders. It is therefore advisable in practice to assess the potential magnitude of such biases. We derive a general adjustment formula for loglinear models of mean cost and explore special cases under plausible assumptions about the distribution of the unmeasured confounder. We assess the performance of the adjustment by simulation, in particular, examining robustness to a key assumption of conditional independence between the unmeasured and measured covariates given the treatment indicator. We apply our method to SEER-Medicare cost data for a stage II/III muscle-invasive bladder cancer cohort. We evaluate the costs for radical cystectomy vs. combined radiation/chemotherapy, and find that the significance of the treatment effect is sensitive to plausible unmeasured Bernoulli, Poisson and Gamma confounders.

Keywords: SEER-Medicare; Sensitivity analysis; censored costs.

PubMed Disclaimer

Figures

Fig. 1
Fig. 1
Bias of treatment effect.
Fig. 2
Fig. 2
Reduction in bias from unadjusted estimate.
Fig. 3
Fig. 3
Coverage of treatment effect.
See this image and copyright information in PMC

References

    1. Arah OA, Chiba Y, Greenland S. Bias formulas for external adjustment and sensitivity analysis of unmeasured confounders. Ann Epidemiol. 2008;18:637–646. - PubMed
    1. Axelson O, Steenland K. Indirect methods of assessing the effects of tobacco use in occupational studies. Am J Ind Med. 1988;13:105–118. - PubMed
    1. Bang H, Tsiatis AA. Estimating medical costs with censored data. Biometrika. 2000;87:329–343.
    1. Bang H, Tsiatis AA. Median regression with censored cost data. Biometrics. 2002;58:643–649. - PubMed
    1. Baris D, Karagas MR, Verrill C, Johnson A, Andrew AS, Marsit CJ, Schwenn M, Colt JS, Cherala S, Samanic C, Waddell R, Cantor KP, Schned A, Rothman N, Lubin J, Fraumeni JF, Hoover RN, Kelsey KT, Silverman DT. A case-control study of smoking and bladder cancer risk: Emergent patterns over time. J Natl Cancer Inst. 2009;101:1553–1561. - PMC - PubMed

LinkOut - more resources