Search for dissertations about: "time-dependent covariates"

Found 4 swedish dissertations containing the words time-dependent covariates.

  2. 1. Multiple Time Scales and Longitudinal Measurements in Event History Analysis

    Author : Danardono; Umeå universitet; []
    Keywords : NATURVETENSKAP; NATURAL SCIENCES; Statistics; Cox regression; multiple events; proportiona hazards; random effects; survival analysis; time-dependent covariates; time origin; Statistik; Statistics; Statistik; Statistics; statistik;

    Abstract : A general time-to-event data analysis known as event history analysis is considered. The focus is on the analysis of time-to-event data using Cox's regression model when the time to the event may be measured from different origins giving several observable time scales and when longitudinal measurements are involved. READ MORE

  4. 2. Reliability analysis and maintenance scheduling considering operating conditions

    Author : Dhananjay Kumar; Luleå tekniska universitet; []
    Keywords : TEKNIK OCH TEKNOLOGIER; ENGINEERING AND TECHNOLOGY; Mining and Rock Engineering; Gruv- och Berganläggningsteknik;

    Abstract : In reliability analysis failure times are often considered as the only factor that can explain the reliability characteristics of a system. This may be insufficient. Operating conditions and other factors (e.g. READ MORE

  5. 3. Generalized survival models as a tool for medical research

    Author : Xingrong Liu; Karolinska Institutet; Karolinska Institutet; []
    Keywords : ;

    Abstract : In medical research, many studies with the time-to-event outcomes investigate the effect of an exposure (or treatment) on patients’ survival. For the analysis of time-to-event or survival data, model-based approaches have been commonly applied. READ MORE

  6. 4. Mathematical programming for optimal probability weighting

    Author : Michele Santacatterina; Karolinska Institutet; Karolinska Institutet; []
    Keywords : ;

    Abstract : In spite of the fact that probability weighting is widely used in statistics to correct for unequal sampling, control for confounding, and handle missing data, it has two main limitations. First, statistical inferences may be inefficient in the presence of extreme probability weights. READ MORE