title: Generalised additive models and hierarchical logistic regression of lameness in dairy cows.
abstract: We examined the relationship between lameness (defined by locomotion score) and four time-related variables using data collected from a study of cattle lameness conducted in the UK from 1998 to 1992. The data were 19,667 locomotion scores for 1790 cows from 27 dairy herds; the four variables were time-from-calving, time of year, parity and time spent in the study. The shape of the relationships between calving and temporal variables and lameness were assessed using loess smoothed terms in a multivariable logistic generalised additive model (GAM). Polynomial relationships derived from the GAM then were included in a Bayesian hierarchical logistic-regression model incorporating between-herd, between-cow and within-cow random effects. The final hierarchical multivariable model showed that the most important variable influencing the probability of lameness was the time of scoring in the study; but, parity, time of year and time-from-calving also were significant. Between-herd and between-cow effects were of roughly equal importance.
mesh_terms: D000818:Animals; D001499:Bayes Theorem; D002417:Cattle; D002418:Cattle Diseases / Q000209:etiology*; D003612:Dairying; D005260:Female; D007774:Lactation; D007794:Lameness, Animal / Q000209:etiology*; D016015:Logistic Models; D008962:Models, Theoretical; D010298:Parity; D036801:Parturition; D011247:Pregnancy; D012307:Risk Factors; D013997:Time Factors