Grant Number:	1R01CA160679-01A1 Interpret this number
Primary Investigator:	Lipsitz, Stuart
Organization:	Brigham And Women'S Hospital
Project Title:	Analyzing National Complex Sample Surveys for Epidemiologic Studies of Cancer
Fiscal Year:	2012

DESCRIPTION (provided by applicant): The ready availability of public-use data from large National population-based complex surveys have immense potential to lead to the assessment of (1) population frequency of cancer (incidence and prevalence); (2) hospital length of stay and related costs for treatment; (3) cancer screening rates; (4) newly discovered associations between risk factors (e.g. screening rates, diet) and different cancers. The goal of this project i to demonstrate this potential using novel statistical methods applied to at least seven United States complex surveys. Specifically, we will use the Behavioral Risk Factor Surveillance System and the Health Information National Trends Survey to describe screening rates; the National Health and Nutrition Examination Survey to explore behaviors (diet, smoking, etc.) in current and future cancer patients; the Nationwide Inpatient Sample and the Medical Expenditure Panel Survey to describe hospital length of stay and related costs for treating cancer; the National Home and Hospice Care Survey to explore end-of-life care for cancer patients; and the National Health Interview Survey to examine follow-up of cancer survivors. Complex sample surveys present some quite unique problems, and we will develop appropriate models and methods complex surveys. Our proposal has three broad aims of significance to medical researchers. (1) New statistical approaches for small subgroup analyses in which the standard large sample complex survey methods can be inappropriate; 2) New statistical procedures for databases that are too large for the usual complex survey approaches to be feasible; and 3) Complex survey methods for skewed data. An additional goal is to make the newly developed statistical/epidemiological methodology widely accessible to non-statisticians. For the methods described in each aim, we plan to create macros and procedures which can be used with existing, widely-used statistical packages (e.g., SAS). Statistical macros and procedures will be documented and made available on the Internet, together with documentation on how to apply these macros to the examples analyzed in the resulting publications. PUBLIC HEALTH RELEVANCE: National complex survey data are used often in cancer epidemiology. We propose new approaches for analyzing such data that are theoretically valid, technically simple and can be implemented within most standard sample survey packages.




A New Bayesian Single Index Model with or without Covariates Missing at Random.
Authors: Dhara K. , Lipsitz S. , Pati D. , Sinha D. .
Source: Bayesian Analysis, 2020 Sep; 15(3), p. 759-780.
EPub date: 2019-08-06 00:00:00.0.
PMID: 33692872
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Semiparametric mixed-scale models using shared Bayesian forests.
Authors: Linero A.R. , Sinha D. , Lipsitz S.R. .
Source: Biometrics, 2020 03; 76(1), p. 131-144.
EPub date: 2019-11-01 00:00:00.0.
PMID: 31222729
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Semiparametric Bayesian latent variable regression for skewed multivariate data.
Authors: Bhingare A. , Sinha D. , Pati D. , Bandyopadhyay D. , Lipsitz S.R. .
Source: Biometrics, 2019 06; 75(2), p. 528-538.
EPub date: 2019-03-29 00:00:00.0.
PMID: 30365158
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Bias-corrected estimates for logistic regression models for complex surveys with application to the United States' Nationwide Inpatient Sample.
Authors: Rader K.A. , Lipsitz S.R. , Fitzmaurice G.M. , Harrington D.P. , Parzen M. , Sinha D. .
Source: Statistical Methods In Medical Research, 2017 Oct; 26(5), p. 2257-2269.
EPub date: 2015-08-11 00:00:00.0.
PMID: 26265769
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Exact Bayesian p-values for a test of independence in a 2 × 2 contingency table with missing data.
Authors: Lin Y. , Lipsitz S.R. , Sinha D. , Fitzmaurice G. , Lipshultz S. .
Source: Statistical Methods In Medical Research, 2017-01-01 00:00:00.0; , p. 962280217702538.
EPub date: 2017-01-01 00:00:00.0.
PMID: 28633606
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Efficient Computation of Reduced Regression Models.
Authors: Lipsitz S.R. , Fitzmaurice G.M. , Sinha D. , Hevelone N. , Giovannucci E. , Trinh Q.D. , Hu J.C. .
Source: The American Statistician, 2017; 71(2), p. 171-176.
EPub date: 2017-02-28 00:00:00.0.
PMID: 29104296
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One-Step Generalized Estimating Equations with Large Cluster Sizes.
Authors: Lipsitz S. , Fitzmaurice G. , Sinha D. , Hevelone N. , Hu J. , Nguyen L.L. .
Source: Journal Of Computational And Graphical Statistics : A Joint Publication Of American Statistical Association, Institute Of Mathematical Statistics, Interface Foundation Of North America, 2017; 26(3), p. 734-737.
EPub date: 2017-07-27 00:00:00.0.
PMID: 29422762
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Approximate median regression for complex survey data with skewed response.
Authors: Fraser R.A. , Lipsitz S.R. , Sinha D. , Fitzmaurice G.M. , Pan Y. .
Source: Biometrics, 2016 Dec; 72(4), p. 1336-1347.
PMID: 27062562
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Testing for independence in J×K contingency tables with complex sample survey data.
Authors: Lipsitz S.R. , Fitzmaurice G.M. , Sinha D. , Hevelone N. , Giovannucci E. , Hu J.C. .
Source: Biometrics, 2015 Sep; 71(3), p. 832-40.
PMID: 25762089
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Using the jackknife for estimation in log link Bernoulli regression models.
Authors: Lipsitz S.R. , Fitzmaurice G.M. , Arriaga A. , Sinha D. , Gawande A.A. .
Source: Statistics In Medicine, 2015-02-10 00:00:00.0; 34(3), p. 444-53.
EPub date: 2015-02-10 00:00:00.0.
PMID: 25388125
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Almost efficient estimation of relative risk regression.
Authors: Fitzmaurice G.M. , Lipsitz S.R. , Arriaga A. , Sinha D. , Greenberg C. , Gawande A.A. .
Source: Biostatistics (oxford, England), 2014 Oct; 15(4), p. 745-56.
PMID: 24705141
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Population-based determinants of radical prostatectomy operative time.
Authors: Carter S.C. , Lipsitz S. , Shih Y.C. , Nguyen P.L. , Trinh Q.D. , Hu J.C. .
Source: Bju International, 2014 May; 113(5b), p. E112-8.
PMID: 24053198
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Simple methods of determining confidence intervals for functions of estimates in published results.
Authors: Fitzmaurice G. , Lipsitz S. , Natarajan S. , Gawande A. , Sinha D. , Greenberg C. , Giovannucci E. .
Source: Plos One, 2014; 9(5), p. e98498.
PMID: 24869806
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Bias correction for the proportional odds logistic regression model with application to a study of surgical complications.
Authors: Lipsitz S.R. , Fitzmaurice G.M. , Regenbogen S.E. , Sinha D. , Ibrahim J.G. , Gawande A.A. .
Source: Journal Of The Royal Statistical Society. Series C, Applied Statistics, 2013 Mar; 62(2), p. 233-250.
PMID: 23913986
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Semiparametric Bayesian Survival Analysis Using Models With Log-linear Median
Authors: Lin J. , Sinha D. , Lipsitz S. , Polpo A. .
Source: Biometrics, 2012 Dec; 68(4), p. 1136-45.
PMID: 23013249
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An extension of the Wilcoxon Rank-Sum test for complex sample survey data.
Authors: Natarajan S. , Lipsitz S.R. , Fitzmaurice G.M. , Sinha D. , Ibrahim J.G. , Haas J. , Gellad W. .
Source: Journal Of The Royal Statistical Society. Series C, Applied Statistics, 2012 Aug; 61(4), p. 653-664.
PMID: 23913985
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Joint generalized estimating equations for multivariate longitudinal binary outcomes with missing data: An application to AIDS data.
Authors: Lipsitz S.R. , Fitzmaurice G.M. , Ibrahim J.G. , Sinha D. , Parzen M. , Lipshultz S. .
Source: Journal Of The Royal Statistical Society. Series A, (statistics In Society), 2009 Jan; 172(1), p. 3-20.
PMID: 20585409
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