Time-to-event data
Discrimination-based sample size calculations for multivariable prognostic models for time-to-event data
... using time-to-event data included were ...missing data, a problem which in general cannot be mit- igated by ...that data are missing at random may be implausible in such datasets, ...
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Use of multi-state models for time-to-event data
... Background & Aim: In medical sciences, the outcome is the time until the occurrence of an event of interest. A multi-state model (MSM) is used to model a process where subjects’ transition takes place ...
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A log-Weibull spatial scan statistic for time to event data
... for time to event ...administrative data from Alberta Health consisting of time from ED dis- charge for an AFF presentation to 1st specialist visit within 365 days in Alberta during ...
12
Semiparametric Methods for Analysis of Randomized Clinical Trials and Arbitrarily Censored Time-to-event Data.
... censored time-to-event data under the mild assumption of a “smooth” density for model components ordinarily left unspecified under a semiparametric per- ...
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Joint models for longitudinal and time-to-event data: a review of reporting quality with a view to meta-analysis
... blank data extraction form is presented in Additional file ...and time-to-event sub-models, types of sub-models, Bayesian or frequentist methods, and software ...and time- to-event ...
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Joint modelling of longitudinal and time-to-event data
... over time, patients dropping out from a clinical trial lead to an incomplete measurement ...missing data are handled incorrectly, then this could lead to attrition ...and time-to-event ...
247
Network meta-analysis of (individual patient) time to event data alongside (aggregate) count data
... for time to healing ...over time, as employed in Soares et al (13) and Woods et al ...the time to event data in the studies for which IPD was ...for time to event outcomes ...
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Network meta-analysis of (individual patient) time to event data alongside (aggregate) count data
... aggregate time to event data presented as hazard ratios (HR), and some measure of uncertainty around these estimates, can be pooled directly using standard methods (analogous to pooling odds ratios ...
11
Semiparametric approaches to inference in joint models for longitudinal and time-to-event data
... the time under the normal scenario (i) and fail to select K = 0 for any of the data sets under the bimodal scenarios (ii) and (iii), with the exception of the conservative BIC procedure under ...
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Practical methods for incorporating summary time to event data into meta analysis
... There is a hierarchy in the methods described [1,2]. The direct methods make no assumptions and are preferable, followed by the various indirect methods based on reported statistics. The curve methods are likely to be ...
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Multistate recursively imputed survival trees for time-to-event data analysis: an application to AIDS and mortality post-HIV infection data
... in data mining and machine learning techniques is random forests (RF); with, random survival forests (RSF) as its extension to sur- vival data analysis ...as time until death, as an endpoint for ...
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On Estimation of Contagion-based Social Network Dependence with Event Time Data.
... on time-to-event ...observed event time, which uses a time-varying covariate to incorporate the network structure and quantify the contagion-based social ...a ...
75
Adjusted estimates for time-to-event endpoints.
... of time-to-event data derived from phase II clinical trials or retrospective studies in hematopoietic cell transplantation (HCT), Cox regression is typically used to quantify the difference in ...
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Proportional Hazards Regression Model for Time to Event Breast Cancer Data: A Bayesian Approach
... the time to ...survival data in a Bayesian framework using Markov Chain Monte Carlo (MCMC) with Gibbs ...improper data analysis if it is not used correctly or choosing inappropriate ...
7
Real-Time Event Centric Data Integration
... (GPR) time-series prediction models for each geo-region G for the time span ...each time t and location G represents the predicted mean value for volume and associated standard deviation for ...of ...
178
4691.pdf
... all time variables are univariate and independent (see Hougaard, ...Recurrent event models, parallel data models, and competing risks models are three common multivariate survival ...Recurrent ...
158
Visual exploration of movement and event data with interactive time masks
... of data are analysed, an appropriate way to present the results of filtering and other operations to the analyst is by applying ...of data filtering after each change of the ...of time masks in ...
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Matching methods to create paired survival data based on an exposure occurring over time: a simulation study with application to breast cancer
... an event occurring over ...the data as if these pairs were a priori known and created at diagnosis, ...at time t = ...correlated data are available such as frailty models [17,18] and marginal ...
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Optimal Dynamic Treatment Regimes from a Classification Perspective for Two Stage Studies with Survival Data.
... an event occur or are censored before the second stage, which means they do not receive a second stage ...the time to event. Patients that do not have an event occur prior to the second stage ...
126
An improved learning based disaster event using big data analytics
... real time mode, drought severity appraisal using settlement data on journal occasion scales, the landslide zonation pilgrimage route in the Himalayas, monitor of the cyclone and harm ...
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