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Modeling Missing Covariate Data and Temporal Features of Time-Dependent Covariates in Tree-Structured Survival Analysis

Lotz, Meredith JoAnne (2009) Modeling Missing Covariate Data and Temporal Features of Time-Dependent Covariates in Tree-Structured Survival Analysis. Doctoral Dissertation, University of Pittsburgh. (Unpublished)

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Tree-structured survival analysis (TSSA) is used to recursively detect covariate values that best divide the sample into subsequent subsets with respect to a time to event outcome. The result is a set of empirical classification groups, each of which identifies individuals with more homogeneous risk than the original sample. We propose methods for managing missing covariate data and also for incorporating temporal features of repeatedly measured covariates into TSSA. First, for missing covariate data, we propose an algorithm that uses a stochastic process to add draws to an existing single tree-structured imputation method. Secondly, to incorporate temporal features of repeatedly measured covariates, we propose two different methods: (1) use a two-stage random effects polynomial model to estimate temporal features of repeatedly measured covariates to be used as TSSA predictor variables, and (2) incorporate other types of functions of repeatedly measured covariates into existing time-dependent TSSA methodology. We conduct simulation studies to assess the accuracy and predictive abilities of our proposed methodology. Our methodology has particular public health importance because we create, interpret and assess TSSA algorithms that can be used in a clinical setting to predict response to treatment for late-life depression.


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Item Type: University of Pittsburgh ETD
Status: Unpublished
CreatorsEmailPitt UsernameORCID
Lotz, Meredith
ETD Committee:
TitleMemberEmail AddressPitt UsernameORCID
Committee ChairAnderson, Stewartsja@pitt.eduSJA
Committee MemberMulsant,
Committee MemberKong, Lanlkong@pitt.eduLKONG
Committee MemberMazumdar, Satimaz1@pitt.eduMAZ1
Date: 29 September 2009
Date Type: Completion
Defense Date: 12 June 2009
Approval Date: 29 September 2009
Submission Date: 20 July 2009
Access Restriction: No restriction; Release the ETD for access worldwide immediately.
Institution: University of Pittsburgh
Schools and Programs: School of Public Health > Biostatistics
Degree: PhD - Doctor of Philosophy
Thesis Type: Doctoral Dissertation
Refereed: Yes
Uncontrolled Keywords: tree-structured survival analysis; temporal features; time-dependent covariates; missing data
Other ID:, etd-07202009-151313
Date Deposited: 10 Nov 2011 19:52
Last Modified: 15 Nov 2016 13:46


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