Global ETD Search
Search theses and dissertations gathered from participating repositories worldwide. Every result links back to the library that holds it. No account is needed.
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Showing 1 to 20 of 22 for “"time-varying covariates"”.
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Approaches for Handling Time-Varying Covariates in Survival Models
Survival models are used in analysing time-to-event data. This type of data is very common in medical research. The Cox proportional hazard model is commonly used in analysing time-to-event data. However, this model is based on the proportional hazard (PH) assumption. Violation of this assumption …
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Linear Models for Multivariate Repeated Measures Data
… analyzing univariate repeated measures data with time varying covariates, (3) derivation of the maximum likelihood estimates of the covariance matrices<strong> V</strong> and <strong>∑ </strong> in the balanced case, (4) derivation of Satterthwaite type approximation to the distribution of …
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On the use of utility billing information for predicting homelessness
… Regression, Cox Proportional Hazard, and the Cox Time Varying Covariates models found these variables to be useful in predicting homelessness. These models were evaluated for prediction using the method of K-Folds and the Cox Time Varying Covariates model was found to have the best performance …
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Statistical inference for residual time quantiles in regression models for censored time-to-event data
… out to develop new methods for the analysis of time-to-event data. In particular, we are concerned with residual time, or the time remaining to an event after a certain amount of time has passed since time zero. We develop methods to estimate quantiles of residual time under a few different …
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A Non-Parametric Framework for Value-Based Individualized Treatment Rule Estimation
… and additionally modified to incorporate time-to-event data with time varying covariates. The proposed ITR estimation techniques are organized into three projects. The first project considers a univariate, continuous, efficacious outcome to be optimized against a binary treatment. A novel …
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Audience Reach Projection for the 2010 FIFA World Cup in South Africa
… a Bayesian multivariate regression with time-varying covariates. Communicating with ESPN executives and analyzing data from the 2010 NCAA March Madness Basketball championship allowed us to identify expected reach patterns for digital platforms. The March Madness dataset also helped us …
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Semiparametric estimation with clustered right censored data via multivariate gaussian random fields
… Data collected on units at all areas include time varying covariates and other environmental factors that may affect event occurrences. The event times in every area can be independent. They can also be correlated with correlation between two units induced by an unobservable frailty. In both …
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Parametric survival models with interval censored data in determining prognostic factors of patients of lung cancer
… where it reflects on the uncertainty of survival time until an event occur. Survival analysis can accommodates both fixed and time varying covariates with the presence of censored data. The survival time of parametric distribution of Weibull, exponential and log-logistic were derived by using the …
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Cox-type model validation with recurrent event data
… is models for the distribution function of the time between events occurrences, especially in the presence of covariates that play a major role in having a better understanding of time to events.</p> <p>This work pertains to statistical inference of the regression parameter and the baseline …
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Exploring Ethnocultural Differences in Distress of Newly Arrived Refugees During Early Resettlement: A Mixed Methods Dissertation
… performed with risk set matching on balancing time-varying covariates across treatment conditions at each time point. Subsequently, a three-way factorial ANOVA was conducted to examine mean differences in distress levels between treatment group, ethnocultural background, and time. In addition, …
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Contributions to the Interface between Experimental Design and Machine Learning
… method under cumulative exposure model for time-to-event data with time-varying covariates. Chapter 6 provides the summary of the entire dissertation.
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Impact Of Time-Varying And Time-Invariant Measures Of Adherence To Secondary Prevention Therapies Post-Acute Myocardial Infarction: An Application Of Marginal Structural Models (MSMS)
… risk of cardiovascular events by using time-invariant and time-varying measures of adherence. The effectiveness of both measures in predicting a (i) recurrent AMI, and (ii) mortality using various mathematical models and statistical techniques was compared. Time dependent confounding was …
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Essays on Welfare Reform and Child Support Enforcement: Evidence From State Administrative Data
… caseload, the multivariate hazard models with time-varying covariates and with individual-specific frailty are estimated. The findings suggest that reform accelerated paternity establishment for non-marital children but slowed down the process of obtaining support orders for open child support …
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Statistical Predictions Based on Accelerated Degradation Data and Spatial Count Data
… developed model is then extended to allow for time-varying covariates and is used to predict outdoor degradation where the explanatory variables are time-varying. Chapter 3 introduces a class of models for analyzing degradation data with dynamic covariate information. We use a general path …
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Heterogeneity modeling and longitudinal clustering
… dosage recommendations for new patients over time. An advantage of our approach is that we do not impose any distribution assumption on estimating random effects. Moreover, the new approach can accommodate general time-varying covariates corresponding to random effects. We show that the …
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Modelling multivariate longitudinal outcomes and time-to-event data
… studies to record information repeatedly over time while observing a time-to-event outcome among subjects. Joint models for longitudinal and survival data simultaneously analyse repetitively measured outcomes and associated event times. They offer valuable applications in two contexts: …
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Essays on Corporate Default Prediction
… of discrete transformation survival models with time-varying covariates is different from the continuous survival models in the literature. Their links and differences are also discussed.</p><p>Essay 2 (Chapter 2) introduces a robust variable selection technique, the least absolute shrinkage and …
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Diagnostics for joint models for longitudinal and survival data
… analyse an outcome repeatedly observed over time such as a bio-marker and associated event times. These models are useful in two practical applications; firstly focusing on survival outcome whilst accounting for time varying covariates measured with error and secondly focusing on the …
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Three Essays on Analyzing and Managing Online Consumer Behavior
… of online multichannel consumer behavior in times of big data. Firms can choose from a plethora of channels to reach consumers on the Internet, such that consumers often use a number of different channels along the customer journey. While the unprecedented availability of individual-level …
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Beyond Parameter Estimation: Analysis of the Case-Cohort Design in Cox Models
… whole cohort. The case-cohort design measures covariates in a random sample (subcohort) of the full cohort, as well as in all cases that emerge, regardless of their initial presence in the subcohort. It is an increasingly popular method, particularly for medical and biological research, due to …
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