Partially hidden multi-state modelling of a prolonged disease state defined by a composite outcome
AbstractFor rheumatic diseases, Minimal Disease Activity (MDA) is usually defined as a composite outcome which is a function of several individual outcomes describing symptoms or quality of life. There is ever increasing interest in MDA but relatively little has been done to characterise the pattern of MDA over time. Motivated by the aim of improving the modelling of MDA in psoriatic arthritis, the use of a two-state model to estimate characteristics of the MDA process is illustrated when there is particular interest in prolonged periods of MDA. Because not all outcomes necessary to define MDA are measured at all clinic vi...
Source: Lifetime Data Analysis - January 19, 2019 Category: Statistics Source Type: research
Semiparametric inference for a two-stage outcome-dependent sampling design with interval-censored failure time data
AbstractWe propose a two-stage outcome-dependent sampling design and inference procedure for studies that concern interval-censored failure time outcomes. This design enhances the study efficiency by allowing the selection probabilities of the second-stage sample, for which the expensive exposure variable is ascertained, to depend on the first-stage observed interval-censored failure time outcomes. In particular, the second-stage sample is enriched by selectively including subjects who are known or observed to experience the failure at an early or late time. We develop a sieve semiparametric maximum pseudo likelihood proce...
Source: Lifetime Data Analysis - January 7, 2019 Category: Statistics Source Type: research
Copula-based score test for bivariate time-to-event data, with application to a genetic study of AMD progression
AbstractMotivated by a genome-wide association study to discover risk variants for the progression of Age-related Macular Degeneration (AMD), we develop a computationally efficient copula-based score test, in which the dependence between bivariate progression times is taken into account. Specifically, a two-step estimation approach with numerical derivatives to approximate the score function and observed information matrix is proposed. Both parametric and weakly parametric marginal distributions under the proportional hazards assumption are considered. Extensive simulation studies are conducted to evaluate the Type I error...
Source: Lifetime Data Analysis - December 17, 2018 Category: Statistics Source Type: research
Robust estimation for panel count data with informative observation times and censoring times
AbstractWe consider the semiparametric regression of panel count data occurring in longitudinal follow-up studies that concern occurrence rate of certain recurrent events. The analysis of panel count data involves two processes, i.e, a recurrent event process of interest and an observation process controlling observation times. However, the model assumptions of existing methods, such as independent censoring time and Poisson assumption, are restrictive and questionable. In this paper, we propose new joint models for panel count data by considering both informative observation times and censoring times. The asymptotic norma...
Source: Lifetime Data Analysis - December 12, 2018 Category: Statistics Source Type: research
Function-based hypothesis testing in censored two-sample location-scale models
AbstractFunction-based hypothesis testing in two-sample location-scale models has been addressed for uncensored data using the empirical characteristic function. A test of adequacy in censored two-sample location-scale models is lacking, however. A plug-in empirical likelihood approach is used to introduce a test statistic, which, asymptotically, is not distribution free. Hence for practical situations bootstrap is necessary for performing the test. A multiplier bootstrap and a model appropriate resampling procedure are given to approximate critical values from the null asymptotic distribution. Although minimum distance es...
Source: Lifetime Data Analysis - December 11, 2018 Category: Statistics Source Type: research
Confidence intervals for the cumulative incidence function via constrained NPMLE
AbstractThe cumulative incidence function (CIF) displays key information in the competing risks setting, which is common in medical research. In this article, we introduce two new methods to compute non-parametric confidence intervals for the CIF. First, we introduce non-parametric profile-likelihood confidence intervals. The method builds on constrained non-parametric maximum likelihood estimation (NPMLE), for which we derive closed-form formulas. This method can be seen as an extension of that of Thomas and Grunkemeier (J Am Stat Assoc 70:865 –871,1975) to the competing risks setting, when the CIF is of interest instea...
Source: Lifetime Data Analysis - December 11, 2018 Category: Statistics Source Type: research
An improved variable selection procedure for adaptive Lasso in high-dimensional survival analysis
AbstractMotivated by high-dimensional genomic studies, we develop an improved procedure for adaptive Lasso in high-dimensional survival analysis. The proposed procedure effectively reduces the false discoveries while successfully maintaining the false negative proportions, which improves the existing adaptive Lasso procedures. The implementation of the proposed procedure is straightforward and it is sufficiently flexible to accommodate large-scale problems where traditional procedures are impractical. To quantify the uncertainty of variable selection and control the family-wise error rate, a multiple sample-splitting based...
Source: Lifetime Data Analysis - November 26, 2018 Category: Statistics Source Type: research
Dealing with death when studying disease or physiological marker: the stochastic system approach to causality
AbstractThe stochastic system approach to causality is applied to situations where the risk of death is not negligible. This approach grounds causality on physical laws, distinguishes system and observation and represents the system by multivariate stochastic processes. The particular role of death is highlighted, and it is shown that local influences must be defined on the random horizon of time of death. We particularly study the problem of estimating the effect of a factorV on a process of interestY, taking death into account. We unify the cases whereY is a counting process (describing an event) and the case whereY is q...
Source: Lifetime Data Analysis - November 17, 2018 Category: Statistics Source Type: research
Nested exposure case-control sampling: a sampling scheme to analyze rare time-dependent exposures
AbstractFor large cohort studies with rare outcomes, the nested case-control design only requires data collection of small subsets of the individuals at risk. These are typically randomly sampled at the observed event times and a weighted, stratified analysis takes over the role of the full cohort analysis. Motivated by observational studies on the impact of hospital-acquired infection on hospital stay outcome, we are interested in situations, where not necessarily the outcome is rare, but time-dependent exposure such as the occurrence of an adverse event or disease progression is. Using the counting process formulation of...
Source: Lifetime Data Analysis - November 13, 2018 Category: Statistics Source Type: research
Estimation for an accelerated failure time model with intermediate states as auxiliary information
AbstractThe accelerated failure time (AFT) model is a common method for estimating the effect of a covariate directly on a patient ’s survival time. In some cases, death is the final (absorbing) state of a progressive multi-state process, however when the survival time for a subject is censored, traditional AFT models ignore the intermediate information from the subject’s most recent disease state despite its relevance to t he mortality process. We propose a method to estimate an AFT model for survival time to the absorbing state that uses the additional data on intermediate state transition times as auxiliary informat...
Source: Lifetime Data Analysis - November 1, 2018 Category: Statistics Source Type: research
Investigating the correlation structure of quadrivariate udder infection times through hierarchical Archimedean copulas
AbstractThe correlation structure imposed on multivariate time to event data is often of a simple nature, such as in the shared frailty model where pairwise correlations between event times in a cluster are all the same. In modeling the infection times of the four udder quarters clustered within the cow, more complex correlation structures are possibly required, and if so, such more complex correlation structures give more insight in the infection process. In this article, we will choose a marginal approach to study more complex correlation structures, therefore leaving the modeling of marginal distributions unaffected by ...
Source: Lifetime Data Analysis - October 1, 2018 Category: Statistics Source Type: research
Survival models and health sequences
AbstractSurvival studies often generate not only a survival time for each patient but also a sequence of health measurements at annual or semi-annual check-ups while the patient remains alive. Such a sequence of random length accompanied by a survival time is called asurvival process. Robust health is ordinarily associated with longer survival, so the two parts of a survival process cannot be assumed independent. This paper is concerned with a general technique —reverse alignment—for constructing statistical models for survival processes, here termedrevival models. A revival model is a regression model in the sense tha...
Source: Lifetime Data Analysis - October 1, 2018 Category: Statistics Source Type: research
Joint model-based clustering of nonlinear longitudinal trajectories and associated time-to-event data analysis, linked by latent class membership: with application to AIDS clinical studies
This article develops a joint modeling approach to a finite mixture of NLME models for longitudinal data and proportional hazard Cox model for time-to-event data, linked by individual latent class indicators, under a Bayesian framework. The proposed joint models and method are applied to a real AIDS clinical trial data set, followed by simulation studies to assess the performance of the proposed joint model and a naive two-step model, in which finite mixture model and Cox model are fitted separately. (Source: Lifetime Data Analysis)
Source: Lifetime Data Analysis - October 1, 2018 Category: Statistics Source Type: research
A semiparametric additive rate model for a modulated renewal process
AbstractRecurrent event data from a long single realization are widely encountered in point process applications. Modeling and analyzing such data are different from those for independent and identical short sequences, and the development of statistical methods requires careful consideration of the underlying dependence structure of the long single sequence. In this paper, we propose a semiparametric additive rate model for a modulated renewal process, and develop an estimating equation approach for the model parameters. The asymptotic properties of the resulting estimators are established by applying the limit theory for ...
Source: Lifetime Data Analysis - October 1, 2018 Category: Statistics Source Type: research
A nonparametric maximum likelihood approach for survival data with observed cured subjects, left truncation and right-censoring
We present the analysis of the motivating SAB study to illustrate the advantages of our model addressing both occurrence and timing of SAB, as compared to existing approaches in practice. (Source: Lifetime Data Analysis)
Source: Lifetime Data Analysis - October 1, 2018 Category: Statistics Source Type: research
