Inference for the median residual life function in sequential multiple assignment randomized trials
dc.contributor.author | Kidwell, Kelley M. | en_US |
dc.contributor.author | Ko, Jin H. | en_US |
dc.contributor.author | Wahed, Abdus S. | en_US |
dc.date.accessioned | 2014-05-23T15:59:35Z | |
dc.date.available | 2015-06-01T15:48:46Z | en_US |
dc.date.issued | 2014-04-30 | en_US |
dc.identifier.citation | Kidwell, Kelley M.; Ko, Jin H.; Wahed, Abdus S. (2014). "Inference for the median residual life function in sequential multiple assignment randomized trials." Statistics in Medicine 33(9): 1503-1513. | en_US |
dc.identifier.issn | 0277-6715 | en_US |
dc.identifier.issn | 1097-0258 | en_US |
dc.identifier.uri | https://hdl.handle.net/2027.42/106925 | |
dc.description.abstract | In survival analysis, median residual lifetime is often used as a summary measure to assess treatment effectiveness; it is not clear, however, how such a quantity could be estimated for a given dynamic treatment regimen using data from sequential randomized clinical trials. We propose a method to estimate a dynamic treatment regimen‐specific median residual life (MERL) function from sequential multiple assignment randomized trials. We present the MERL estimator, which is based on inverse probability weighting, as well as, two variance estimates for the MERL estimator. One variance estimate follows from Lunceford, Davidian and Tsiatis' 2002 survival function‐based variance estimate and the other uses the sandwich estimator. The MERL estimator is evaluated, and its two variance estimates are compared through simulation studies, showing that the estimator and both variance estimates produce approximately unbiased results in large samples. To demonstrate our methods, the estimator has been applied to data from a sequentially randomized leukemia clinical trial. Copyright © 2013 John Wiley & Sons, Ltd. | en_US |
dc.publisher | Wiley Periodicals, Inc. | en_US |
dc.publisher | SIAM | en_US |
dc.subject.other | Dynamic Treatment Regimen | en_US |
dc.subject.other | Adaptive Treatment Strategy | en_US |
dc.subject.other | Inverse Probability Weighting | en_US |
dc.subject.other | Median Residual Life Function | en_US |
dc.subject.other | Sequential Randomization | en_US |
dc.subject.other | Non‐Parametric Estimation | en_US |
dc.title | Inference for the median residual life function in sequential multiple assignment randomized trials | en_US |
dc.type | Article | en_US |
dc.rights.robots | IndexNoFollow | en_US |
dc.subject.hlbsecondlevel | Statistics and Numeric Data | en_US |
dc.subject.hlbsecondlevel | Public Health | en_US |
dc.subject.hlbsecondlevel | Medicine (General) | en_US |
dc.subject.hlbtoplevel | Social Sciences | en_US |
dc.subject.hlbtoplevel | Health Sciences | en_US |
dc.subject.hlbtoplevel | Science | en_US |
dc.description.peerreviewed | Peer Reviewed | en_US |
dc.description.bitstreamurl | http://deepblue.lib.umich.edu/bitstream/2027.42/106925/1/sim6042.pdf | |
dc.identifier.doi | 10.1002/sim.6042 | en_US |
dc.identifier.source | Statistics in Medicine | en_US |
dc.identifier.citedreference | Song JK, Cho GY. A note on percentile residual life. Sankhya 1995; 57: 333 – 335. | en_US |
dc.identifier.citedreference | Csorgo M, S C. Estimation of percentile residual life. Operations Research 1987; 35: 598 – 605. | en_US |
dc.identifier.citedreference | Chung CF. Confidence bands for percentile residual lifetime under random censorship mode. Journal of Multivariate Analysis 1989; 29: 94 – 126. | en_US |
dc.identifier.citedreference | Feng Z, Kulasekera KB. Nonparametric estimation of the percentile residual life function. Communications in Statistics‐ Theory and Methods 1991; 20: 87 – 105. | en_US |
dc.identifier.citedreference | Lillo RE. On the median residual lifetime and its aging properties: a characterization theorem and applications. Naval Research Logistics 2005; 4: 370 – 380. | en_US |
dc.identifier.citedreference | Holland PW. Statistics and causal inference. Journal of the American Statistical Association 1986; 81: 945 – 60. | en_US |
dc.identifier.citedreference | Wahed AS, Tsiatis AA. Optimal estimator for the survival distribution and related quantities for treatment policies in two‐stage randomization designs in clinical trials. Biometrics 2004; 60: 124 – 133. | en_US |
dc.identifier.citedreference | Wahed AS, Tsiatis AA. Semi‐parametric efficient estimation of the survival distribution for treatment policies in two‐stage randomization designs in clinical trials with censored data. Biometrika 2006; 93: 147 – 161. | en_US |
dc.identifier.citedreference | Guo X, Tsiatis AA. A weighted risk set estimator for survival distributions in two‐stage randomization designs with censored survival data. The International Journal of Biostatistics 2005; 1: 1 – 15. | en_US |
dc.identifier.citedreference | Schmittlein DC, Morrison DG. The median residual lifetime: a characterization theorem and an application. Operations Research 1981; 29 ( 2 ): 392 – 399. | en_US |
dc.identifier.citedreference | Haines AL, Singpurwalla ND. Some contributions to the stochastic characterization of wear. In Reliability and Biometry, Proschan F, Serfling RJ (eds). SIAM: Philadelphia, 1974. | en_US |
dc.identifier.citedreference | Arnold BC, Brokett PL. When does the β th percentile residual life function determine the distribution? Operations Research 1983; 31: 391 – 396. | en_US |
dc.identifier.citedreference | Joe H, Proschan F. Percentile residual life functions. Operations Research 1984; 32: 668 – 678. | en_US |
dc.identifier.citedreference | Joe H. Characterizations of life distributions from percentile residual lifetimes. Annals of the Insititue for Statistical Mathematics 1985; 37: 165 – 172. | en_US |
dc.identifier.citedreference | Ko JH. Statistical issues in the design and analysis of sequentially randomized trials. Ph.D. Thesis, Department of Biostatistics, University of Pittsburgh, 2010. | en_US |
dc.identifier.citedreference | Kidwell KM, Wahed AS. Weighted log‐rank statistic to compare shared‐path adaptive treatment strategies. Biostatistics 2013; 14 ( 2 ). | en_US |
dc.identifier.citedreference | Stefanski LA, Boos DD. The calculus of m‐estimation. The American Statistician 2002; 56 ( 1 ): 29 – 38. | en_US |
dc.identifier.citedreference | Jeong J, Jung S, Costantino J. Nonparametric inference on median residual lifetimes in breast cancer patients. Biometrics 2008; 64: 157 – 163. | en_US |
dc.identifier.citedreference | Cole SR, Frangakis CE. The consistency statement in causal inference: a definition or an assumption? Epidemiology 2009; 20 ( 1 ): 3 – 5. | en_US |
dc.identifier.citedreference | Murphy SA. An experimental design for the development of adaptive treatment strategies. Statistical Methods 2005; 24: 1455 – 81. | en_US |
dc.identifier.citedreference | Lavori PW, Dawson R, J RA. Flexible treatment strategies in chronic disease: clinical research implications. Biological Psychology 2000; 48: 605 – 614. | en_US |
dc.identifier.citedreference | Stone RM, Berg DT, George SL, Dodge RK, Paciucci PA, Schulman P, Lee EJ, Moore JO, Powell BL, Schiffer CA. Granulocytemacrophage colony‐stimulating factor after initial chemotherapy for elderly patients with primary acute myelogenous leukemia. The New England Journal of Medicine 1995; 332: 1671 – 1677. | en_US |
dc.identifier.citedreference | Stone RM, Berg DT, George SL, Dodge RK, Paciucci PA, Schulman P, Lee EJ, Moore JO, Powell BL, Baer MR, Bloomfield CD, Schiffer CA. Postremission therapy in older patients with de novo acute myeloid leukemia: a randomized trial comparing mitoxantrone and intermediate‐dose cytarabine with standard‐dose cytarabine. Blood 2001; 98: 548 – 553. | en_US |
dc.identifier.citedreference | Lunceford JK, Davidian M, Tsiatis AA. Estimation of survival distributions of treatment policies in two‐stage randomization designs in clinical trials. Biometrics 2002; 58: 48 – 57. | en_US |
dc.identifier.citedreference | Robins JM, Rotnitzky A, Zhao LP. Estimation of regression coefficients when some regressors are not always observed. Journal of American Statistical Association 1994; 89: 846 – 866. | en_US |
dc.owningcollname | Interdisciplinary and Peer-Reviewed |
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