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Grant Details

Grant Number: 5R01CA082370-10 Interpret this number
Primary Investigator: Neuhaus, John
Organization: University Of California, San Francisco
Project Title: Assessing / Developing Methods for Complex Dependent Data
Fiscal Year: 2013


Abstract

DESCRIPTION (provided by applicant): Dependent data methods are widely used in practice to conduct analyses for hierarchical and longitudinal studies. Formally, their use depends on a variety of assumptions, for example, parametric distributional assumptions or assumptions about the sampling mechanism. The overarching goal of our research program is to quantify sensitivity to these assumptions, identifying scenarios in which they are and are not important and developing new, more robust methods when necessary. Our focus is on assumptions surrounding the sampling mechanism, including missing data and outcome dependent sampling. Our research has four aims. Our first aim considers the performance of commonly used methods that are used to avoid cluster level confounding. However, they may be sensitive to data which are missing at random (MAR), but not missing completely at random (MCAR). Aims 2 through 4 consider outcome dependent sampling mechanisms that are frequently encountered in practice. In Aim 2 we consider the use of parametric mixed models in situations such as for outcome dependent family studies. Aim 3 considers the situation in which the timing of measurements may be dependent on previous results (e.g., more frequent exams in prostate cancer patients with rising prostate specific antigen (PSA) test results). Aim 4 considers a general and unifying context in which to imbed the work on Aims 2 and 3, derive optimality results, and develop a platform for creation of new statistical methods for outcome dependent sampling. Results from our research will directly inform current statistical practice for these commonly used methods.



Publications

Biased and unbiased estimation in longitudinal studies with informative visit processes.
Authors: McCulloch C.E. , Neuhaus J.M. , Olin R.L. .
Source: Biometrics, 2016 12; 72(4), p. 1315-1324.
EPub date: 2016-03-17.
PMID: 26990830
Related Citations

A Prospective Comparison of Informant-based and Performance-based Dementia Screening Tools to Predict In-Hospital Delirium.
Authors: Zeng L. , Josephson S.A. , Fukuda K.A. , Neuhaus J. , Douglas V.C. .
Source: Alzheimer disease and associated disorders, 2015 Oct-Dec; 29(4), p. 312-6.
PMID: 25350550
Related Citations

COVARIATE DECOMPOSITION METHODS FOR LONGITUDINAL MISSING-AT-RANDOM DATA AND PREDICTORS ASSOCIATED WITH SUBJECT-SPECIFIC EFFECTS.
Authors: Neuhaus J.M. , McCulloch C.E. .
Source: Australian & New Zealand journal of statistics, 2014 Dec; 56(4), p. 331-345.
PMID: 26052246
Related Citations

Likelihood-based analysis of longitudinal data from outcome-related sampling designs.
Authors: Neuhaus J.M. , Scott A.J. , Wild C.J. , Jiang Y. , McCulloch C.E. , Boylan R. .
Source: Biometrics, 2014 Mar; 70(1), p. 44-52.
EPub date: 2013-11-21.
PMID: 24571396
Related Citations

Impact of gender and blood pressure on poststroke cognitive decline among older Latinos.
Authors: Levine D.A. , Haan M.N. , Langa K.M. , Morgenstern L.B. , Neuhaus J. , Lee A. , Lisabeth L.D. .
Source: Journal of stroke and cerebrovascular diseases : the official journal of National Stroke Association, 2013 Oct; 22(7), p. 1038-45.
EPub date: 2012-06-27.
PMID: 22748715
Related Citations

Medication adherence: tailoring the analysis to the data.
Authors: Saberi P. , Johnson M.O. , McCulloch C.E. , Vittinghoff E. , Neilands T.B. .
Source: AIDS and behavior, 2011 Oct; 15(7), p. 1447-53.
PMID: 21833689
Related Citations

The effect of misspecification of random effects distributions in clustered data settings with outcome-dependent sampling.
Authors: Neuhaus J.M. , McCulloch C.E. .
Source: The Canadian journal of statistics = Revue canadienne de statistique, 2011-09-01; 39(3), p. 488-497.
EPub date: 2011-07-27.
PMID: 23204632
Related Citations

A note on type II error under random effects misspecification in generalized linear mixed models.
Authors: Neuhaus J.M. , McCulloch C.E. , Boylan R. .
Source: Biometrics, 2011 Jun; 67(2), p. 654-6; disucssion 656-60.
PMID: 21689077
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Prediction of random effects in linear and generalized linear models under model misspecification.
Authors: McCulloch C.E. , Neuhaus J.M. .
Source: Biometrics, 2011 Mar; 67(1), p. 270-9.
PMID: 20528860
Related Citations

An open-label study of memantine treatment in 3 subtypes of frontotemporal lobar degeneration.
Authors: Boxer A.L. , Lipton A.M. , Womack K. , Merrilees J. , Neuhaus J. , Pavlic D. , Gandhi A. , Red D. , Martin-Cook K. , Svetlik D. , et al. .
Source: Alzheimer disease and associated disorders, 2009 Jul-Sep; 23(3), p. 211-7.
PMID: 19812461
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Clinical-neuroimaging characteristics of dysexecutive mild cognitive impairment.
Authors: Pa J. , Boxer A. , Chao L.L. , Gazzaley A. , Freeman K. , Kramer J. , Miller B.L. , Weiner M.W. , Neuhaus J. , Johnson J.K. .
Source: Annals of neurology, 2009 Apr; 65(4), p. 414-23.
PMID: 19399879
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