journal
MENU ▼
Read by QxMD icon Read
search

Lifetime Data Analysis

journal
https://read.qxmd.com/read/30734884/multiplicative-rates-model-for-recurrent-events-in-case-cohort-studies
#1
Poulami Maitra, Leila D A F Amorim, Jianwen Cai
In large prospective cohort studies, accumulation of covariate information and follow-up data make up the majority of the cost involved in the study. This might lead to the study being infeasible when there are some expensive variables and/or the event is rare. Prentice (Biometrika 73(1):1-11, 1986) proposed the case-cohort study for time to event data to tackle this problem. There has been extensive research on the analysis of univariate and clustered failure time data, where the clusters are formed among different individuals under case-cohort sampling scheme...
February 8, 2019: Lifetime Data Analysis
https://read.qxmd.com/read/30734137/frailty-modelling-approaches-for-semi-competing-risks-data
#2
Il Do Ha, Liming Xiang, Mengjiao Peng, Jong-Hyeon Jeong, Youngjo Lee
In the semi-competing risks situation where only a terminal event censors a non-terminal event, observed event times can be correlated. Recently, frailty models with an arbitrary baseline hazard have been studied for the analysis of such semi-competing risks data. However, their maximum likelihood estimator can be substantially biased in the finite samples. In this paper, we propose effective modifications to reduce such bias using the hierarchical likelihood. We also investigate the relationship between marginal and hierarchical likelihood approaches...
February 7, 2019: Lifetime Data Analysis
https://read.qxmd.com/read/30697652/modeling-marginal-features-in-studies-of-recurrent-events-in-the-presence-of-a-terminal-event
#3
Per Kragh Andersen, Jules Angst, Henrik Ravn
We study models for recurrent events with special emphasis on the situation where a terminal event acts as a competing risk for the recurrent events process and where there may be gaps between periods during which subjects are at risk for the recurrent event. We focus on marginal analysis of the expected number of events and show that an Aalen-Johansen type estimator proposed by Cook and Lawless is applicable in this situation. A motivating example deals with psychiatric hospital admissions where we supplement with analyses of the marginal distribution of time to the competing event and the marginal distribution of the time spent in hospital...
January 29, 2019: Lifetime Data Analysis
https://read.qxmd.com/read/30661194/partially-hidden-multi-state-modelling-of-a-prolonged-disease-state-defined-by-a-composite-outcome
#4
Vernon T Farewell, Li Su, Christopher Jackson
For 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...
January 19, 2019: Lifetime Data Analysis
https://read.qxmd.com/read/30617753/semiparametric-inference-for-a-two-stage-outcome-dependent-sampling-design-with-interval-censored-failure-time-data
#5
Qingning Zhou, Jianwen Cai, Haibo Zhou
We 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...
January 7, 2019: Lifetime Data Analysis
https://read.qxmd.com/read/30560439/copula-based-score-test-for-bivariate-time-to-event-data-with-application-to-a-genetic-study-of-amd-progression
#6
Tao Sun, Yi Liu, Richard J Cook, Wei Chen, Ying Ding
Motivated 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...
December 17, 2018: Lifetime Data Analysis
https://read.qxmd.com/read/30542803/robust-estimation-for-panel-count-data-with-informative-observation-times-and-censoring-times
#7
Hangjin Jiang, Wen Su, Xingqiu Zhao
We 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...
December 12, 2018: Lifetime Data Analysis
https://read.qxmd.com/read/30539364/confidence-intervals-for-the-cumulative-incidence-function-via-constrained-npmle
#8
Paul Blanche
The 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 instead of the survival function...
December 11, 2018: Lifetime Data Analysis
https://read.qxmd.com/read/30539363/function-based-hypothesis-testing-in-censored-two-sample-location-scale-models
#9
Sundarraman Subramanian
Function-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...
December 11, 2018: Lifetime Data Analysis
https://read.qxmd.com/read/30478713/an-improved-variable-selection-procedure-for-adaptive-lasso-in-high-dimensional-survival-analysis
#10
Kevin He, Yue Wang, Xiang Zhou, Han Xu, Can Huang
Motivated 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 testing algorithm is developed...
November 26, 2018: Lifetime Data Analysis
https://read.qxmd.com/read/30448970/dealing-with-death-when-studying-disease-or-physiological-marker-the-stochastic-system-approach-to-causality
#11
Daniel Commenges
The 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 factor V on a process of interest Y, taking death into account...
November 17, 2018: Lifetime Data Analysis
https://read.qxmd.com/read/30426275/nested-exposure-case-control-sampling-a-sampling-scheme-to-analyze-rare-time-dependent-exposures
#12
Jan Feifel, Madlen Gebauer, Martin Schumacher, Jan Beyersmann
For 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...
November 13, 2018: Lifetime Data Analysis
https://read.qxmd.com/read/30386969/estimation-for-an-accelerated-failure-time-model-with-intermediate-states-as-auxiliary-information
#13
Ritesh Ramchandani, Dianne M Finkelstein, David A Schoenfeld
The 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 the 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 information when a patient is right censored...
November 1, 2018: Lifetime Data Analysis
https://read.qxmd.com/read/30083977/commentary-alignment-of-time-scales-and-joint-models
#14
Kwun Chuen Gary Chan
No abstract text is available yet for this article.
October 2018: Lifetime Data Analysis
https://read.qxmd.com/read/30076510/response-to-discussants-of-survival-models-and-health-sequences
#15
Walter Dempsey, Peter McCullagh
Survival 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 a survival 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 termed revival models...
October 2018: Lifetime Data Analysis
https://read.qxmd.com/read/30022323/contribution-to-the-discussion-of-survival-models-and-health-sequences-by-w-dempsey-and-p-mccullagh
#16
Per Kragh Andersen
No abstract text is available yet for this article.
October 2018: Lifetime Data Analysis
https://read.qxmd.com/read/30022322/commentary-to-the-paper-by-walter-dempsey-and-peter-mccullagh
#17
Hans C van Houwelingen
No abstract text is available yet for this article.
October 2018: Lifetime Data Analysis
https://read.qxmd.com/read/29961227/editorial-to-accompany-the-discussion-paper-survival-models-and-health-sequences-by-walter-dempsey-and-peter-mccullagh
#18
EDITORIAL
Niels Keiding
No abstract text is available yet for this article.
October 2018: Lifetime Data Analysis
https://read.qxmd.com/read/29502184/survival-models-and-health-sequences
#19
Walter Dempsey, Peter McCullagh
Survival 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 a survival 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 termed revival models...
October 2018: Lifetime Data Analysis
https://read.qxmd.com/read/29374340/illness-death-model-statistical-perspective-and-differential-equations
#20
Ralph Brinks, Annika Hoyer
The aim of this work is to relate the theory of stochastic processes with the differential equations associated with multistate (compartment) models. We show that the Kolmogorov Forward Differential Equations can be used to derive a relation between the prevalence and the transition rates in the illness-death model. Then, we prove mathematical well-definedness and epidemiological meaningfulness of the prevalence of the disease. As an application, we derive the incidence of diabetes from a series of cross-sections...
October 2018: Lifetime Data Analysis
journal
journal
32387
1
2
Fetch more papers »
Fetching more papers... Fetching...
Read by QxMD. Sign in or create an account to discover new knowledge that matter to you.
Remove bar
Read by QxMD icon Read
×

Search Tips

Use Boolean operators: AND/OR

diabetic AND foot
diabetes OR diabetic

Exclude a word using the 'minus' sign

Virchow -triad

Use Parentheses

water AND (cup OR glass)

Add an asterisk (*) at end of a word to include word stems

Neuro* will search for Neurology, Neuroscientist, Neurological, and so on

Use quotes to search for an exact phrase

"primary prevention of cancer"
(heart or cardiac or cardio*) AND arrest -"American Heart Association"