Inference for outcome probabilities in multi-state models.
In bone marrow transplantation studies, patients are followed over time and a number of events may be observed. These include both ultimate events like death and relapse and transient events like graft versus host disease and graft recovery. Such studies, therefore, lend themselves for using an analytic approach based on multi-state models. We will give a review of such methods with emphasis on regression models for both transition intensities and transition- and state occupation probabilities. Both semi-parametric models, like the Cox regression model, and parametric models based on piecewise constant intensities will be discussed.
Andersen
Per Kragh
PK
Department of Biostatistics, University of Copenhagen, O. Farimagsgade 5, PB 2099, 1014, Copenhagen K, Denmark. P.K.Andersen@biostat.ku.dk
Pohar Perme
Maja
M
D016026:Bone Marrow Transplantation / Q000009:adverse effects* / Q000401:mortality / Q000706:statistics & numerical data*; D003627:Data Interpretation, Statistical; D006801:Humans; D015233:Models, Statistical; D017063:Outcome Assessment, Health Care / Q000706:statistics & numerical data*; D016016:Proportional Hazards Models; D012044:Regression Analysis; D018709:Statistics, Nonparametric; D013269:Stochastic Processes; D016019:Survival Analysis
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