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A flexible semiparametric modeling approach for doubly censored data with an application to prostate cancer.Meta-analysis of time-to-event outcomes from randomized trials using restricted mean survival time: application to individual participant data.Instrumental variable method for time-to-event data using a pseudo-observation approach.Bias and precision of methods for estimating the difference in restricted mean survival time from an individual patient data meta-analysis.Inherited GATA3 variants are associated with Ph-like childhood acute lymphoblastic leukemia and risk of relapse.IQ and mental health are vital predictors of work drop out and early mortality. Multi-state analyses of Norwegian male conscripts.Multiple imputation based on restricted mean model for censored data.Model-based estimation of measures of association for time-to-event outcomes.Contrasting treatment-specific survival using double-robust estimators.Restricted mean survival time: an alternative to the hazard ratio for the design and analysis of randomized trials with a time-to-event outcome.Augmenting the logrank test in the design of clinical trials in which non-proportional hazards of the treatment effect may be anticipated.The Use of Physiotherapy among Patients with Subacromial Impingement Syndrome: Impact of Sex, Socio-Demographic and Clinical FactorsAbsolute risk regression for competing risks: interpretation, link functions, and predictionPseudo-observations for competing risks with covariate dependent censoring.Competing risks in epidemiology: possibilities and pitfalls.Comparing predictions among competing risks models with time-dependent covariates.The health and economic burden of bloodstream infections caused by antimicrobial-susceptible and non-susceptible Enterobacteriaceae and Staphylococcus aureus in European hospitals, 2010 and 2011: a multicentre retrospective cohort study.Applying competing risks regression models: an overview.Comparison of stopped Cox regression with direct methods such as pseudo-values and binomial regression.The clinical course of cirrhosis: The importance of multistate models and competing risks analysis.A joint modelling approach for multistate processes subject to resolution and under intermittent observations.Causal inference in survival analysis using pseudo-observations.Modeling restricted mean survival time under general censoring mechanisms.Considerations for Comprehensive Analyses of Sporozoite-Based Controlled Human Malaria Infection Studies.Flexible parametric modelling of the cause-specific cumulative incidence function.A random forest approach for competing risks based on pseudo-values.The effect of health insurance on childhood cancer survival in the United States.Comparisons of the performance of different statistical tests for time-to-event analysis with confounding factors: practical illustrations in kidney transplantation.Stagewise pseudo-value regression for time-varying effects on the cumulative incidence.Regression models for expected length of stay.Toward a more complete understanding of the association between a hepatitis C sustained viral response and cause-specific outcomes.Regression modeling of the cumulative incidence function with missing causes of failure using pseudo-values.Calibration plots for risk prediction models in the presence of competing risks.The use of restricted mean survival time to estimate the treatment effect in randomized clinical trials when the proportional hazards assumption is in doubt.Recurrent tuberculosis in Finland 1995-2013: a clinical and epidemiological cohort study.A simple, doubly robust, efficient estimator for survival functions using pseudo observations.Optimal threshold estimator of a prognostic marker by maximizing a time-dependent expected utility function for a patient-centered stratified medicine.Long-chain n-3 and n-6 polyunsaturated fatty acids and risk of atrial fibrillation: Results from a Danish cohort study.Assessing the effect of a partly unobserved, exogenous, binary time-dependent covariate on survival probabilities using generalised pseudo-values.ROBUST MIXED EFFECTS MODEL FOR CLUSTERED FAILURE TIME DATA: APPLICATION TO HUNTINGTON'S DISEASE EVENT MEASURES.
P2860
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P2860
description
article científic
@ca
article scientifique
@fr
articolo scientifico
@it
artigo científico
@pt
bilimsel makale
@tr
scientific article published on 04 August 2009
@en
vedecký článok
@sk
vetenskaplig artikel
@sv
videnskabelig artikel
@da
vědecký článek
@cs
name
Pseudo-observations in survival analysis.
@en
Pseudo-observations in survival analysis.
@nl
type
label
Pseudo-observations in survival analysis.
@en
Pseudo-observations in survival analysis.
@nl
prefLabel
Pseudo-observations in survival analysis.
@en
Pseudo-observations in survival analysis.
@nl
P356
P1476
Pseudo-observations in survival analysis.
@en
P2093
Per Kragh Andersen
P356
10.1177/0962280209105020
P577
2009-08-04T00:00:00Z