Inference for outcome probabilities in multi-state models
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Publication:841031
DOI10.1007/s10985-008-9097-xzbMath1302.62226OpenAlexW2024715750WikidataQ37268888 ScholiaQ37268888MaRDI QIDQ841031
Maja Pohar Perme, Per Kragh Andersen
Publication date: 14 September 2009
Published in: Lifetime Data Analysis (Search for Journal in Brave)
Full work available at URL: http://europepmc.org/articles/pmc2735091
Applications of statistics to biology and medical sciences; meta analysis (62P10) Medical applications (general) (92C50)
Related Items (11)
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Uses Software
Cites Work
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- On pseudo-values for regression analysis in competing risks models
- Multi-state models: A review
- Validity of the Aalen-Johansen estimators of stage occupation probabilities and Nelson-Aalen estimators of integrated transition hazards for non-Markov models
- Multi-state models in epidemiology
- Asymptotic theory for the Cox semi-Markov illness-death model
- Dynamic regression models for survival data.
- Extensions and Applications of the Cox‐Aalen Survival Model
- A Markov Model for Analysing Cancer Markers and Disease States in Survival Studies
- Inference for Events With Dependent Risks in Multiple Endpoint Studies
- Regression modeling of competing crude failure probabilities
- Semiparametric Regression for the Mean and Rate Functions of Recurrent Events
- A Proportional Hazards Model for the Subdistribution of a Competing Risk
- Prediction of Cumulative Incidence Function under the Proportional Hazards Model
- Confidence Bands for Cumulative Incidence Curves Under the Additive Risk Model
- Multi-state models for event history analysis
- Multi-state models for bone marrow transplantation studies
- Inference for multi-state models from interval-censored data
- Regression Analysis for Multistate Models Based on a Pseudo‐value Approach, with Applications to Bone Marrow Transplantation Studies
- Direct Modelling of Regression Effects for Transition Probabilities in Multistate Models
- Additive hazards Markov regression models illustrated with bone marrow transplant data
- Regression Modeling of Competing Risks Data Based on Pseudovalues of the Cumulative Incidence Function
- Statistical models based on counting processes
- Nonparametric estimation of transition probabilities in a non-Markov illness-death model
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