Dai, James Y and LeBlanc, Michael and Kooperberg, Charles (2009) Semiparametric estimation exploiting covariate independence in two-phase randomized trials. Biometrics, 65 (1). pp. 178-187. ISSN 1541-0420
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Abstract
Recent results for case-control sampling suggest when the covariate distribution is constrained by gene-environment independence, semiparametric estimation exploiting such independence yields a great deal of efficiency gain. We consider the efficient estimation of the treatment-biomarker interaction in two-phase sampling nested within randomized clinical trials, incorporating the independence between a randomized treatment and the baseline markers. We develop a Newton-Raphson algorithm based on the profile likelihood to compute the semiparametric maximum likelihood estimate (SPMLE). Our algorithm accommodates both continuous phase-one outcomes and continuous phase-two biomarkers. The profile information matrix is computed explicitly via numerical differentiation. In certain situations where computing the SPMLE is slow, we propose a maximum estimated likelihood estimator (MELE), which is also capable of incorporating the covariate independence. This estimated likelihood approach uses a one-step empirical covariate distribution, thus is straightforward to maximize. It offers a closed-form variance estimate with limited increase in variance relative to the fully efficient SPMLE. Our results suggest exploiting the covariate independence in two-phase sampling increases the efficiency substantially, particularly for estimating treatment-biomarker interactions.
| Item Type: | Article or Abstract |
|---|---|
| Additional Information: | This article is available to subscribers only via the URL above. |
| DOI: | 10.1111/j.1541-0420.2008.01046.x |
| PubMed ID: | 18479485 |
| NIHMSID: | NIHMS107483 |
| PMCID: | PMC2892338 |
| Grant Numbers: | R01 CA074841-09, U01 CA125489-03, P01 CA053996-31 |
| Keywords or MeSH Headings: | * Algorithms * Biological Markers * Biometry/methods* * Data Interpretation, Statistical * Humans * Models, Theoretical * Randomized Controlled Trials as Topic/statistics & numerical data* * Treatment Outcome |
| Subjects: | Research Methodologies > Clinical Trials Research Methodologies > Mathematics and statistics |
| Depositing User: | Library Staff |
| Date Deposited: | 02 Apr 2009 22:01 |
| Last Modified: | 14 Feb 2012 14:42 |
| URI: | http://authors.fhcrc.org/id/eprint/272 |
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