By Lee, L. A., Journal of Dairy Science, 1989
Description
Survival analysis, a regression technique for analyzing data in which the time to an event is the measured outcome, was used to quantify the effects of five common herd diseases on days open in dairy cattle. Data were collected retrospectively from health and production records of 467 cows in five herds. In the 5-yr study period, 1059 lactations were followed to a conception or culling event. Retained placenta, nonsystemic metritis, systemic metritis, ovarian cysts, and lameness were associated with a decrease in conception rate and an increase in median days open. The hazard ratios for conception were .66, .83, .70, .70, and .69 and the increase in median days open 5, 15, 13, 22, and 28 d for the five diseases, respectively. Several attributes of survival analysis make it a valuable tool for quantifying days open in dairy cattle, including the ability to use reproductive information from observations which fail to conceive. Additionally, results obtained from survival analysis complement economic and decision analyses and will facilitate accurate cost assessment of suboptimal reproductive performance
Survival analysis, a regression technique for analyzing data in which the time to an event is the measured outcome, was used to quantify the effects of five common herd diseases on days open in dairy cattle. Data were collected retrospectively from health and production records of 467 cows in five herds. In the 5-yr study period, 1059 lactations were followed to a conception or culling event. Retained placenta, nonsystemic metritis, systemic metritis, ovarian cysts, and lameness were associated with a decrease in conception rate and an increase in median days open. The hazard ratios for conception were .66, .83, .70, .70, and .69 and the increase in median days open 5, 15, 13, 22, and 28 d for the five diseases, respectively. Several attributes of survival analysis make it a valuable tool for quantifying days open in dairy cattle, including the ability to use reproductive information from observations which fail to conceive. Additionally, results obtained from survival analysis complement economic and decision analyses and will facilitate accurate cost assessment of suboptimal reproductive performance
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