Comparison of Parameters and Fitness of Different Time-dependent and Time-Independent Independent Variables in Survival Analysis

• Main Authors: H Sharifi, AA Haghdoost
• Format: Article
• Language: fas
• Published: Tehran University of Medical Sciences 2015-06-01
• Series: مجله اپیدمیولوژی ایران
• Subjects: Survival analysis; Time-dependent and time-independent models; Lexis expansion; Dairy cows
• Online Access: http://irje.tums.ac.ir/browse.php?a_code=A-10-25-5107&slc_lang=en&sid=1

Background & Objectives : Management of time-dependent variables is the advantages of survival analysis. This study compares time-dependent and -independent variables in survival analysis in culling of dairy cows.   Methods: In this historical cohort, 7067 dairy cows in the Province of Tehran were recruited. Cows were followed to the next calving or culling. Data on the occurrence of health disorders, calving season, parity, and milk production was obtained. Model 1 treated diseases as time-independent covariates. In models 2, up to 5 diseases were considered time-dependent covariates. For each observation, we split follow-up time in intervals each corresponding to a different lactation month using Lexis expansion of the original dataset. Model 2 assumed that an animal experienced a certain disease from the beginning of the occurrence of that disease by the end of the period. Model 3 assumed that cows were at risk from the begging of the study until the disease occurred (inverse of model 2). In models 4 and 5, an animal was assumed to experience a certain disease for 1 month if the disease occurred during this period. In Model 4 assumed diseases occurred only one time, and in model 5, multiple disease occurrences at different months were considered as different episodes.   Results : AIC in model 1 and 5 was 10809 and 10366 moreover, BIC was 10926 and 10528. According to this numbers and the shape of the Cox-Snell Residuals, model 5 with Gompertz distribution was the best model.   Conclusion : Models without time dependency tended to seriously underestimate the risk of a disease on culling.