Thesis supervisor: Zsolt Lang
co-supervisor: László Ózsvári
Location of studies (in Hungarian): University of Veterinary Medicine Abbreviation of location of studies: ATE
Description of the research topic:
The relationship between prevalence of infectious diseases and animal management conditions, age, herd size etc. is investigated in dairy cattle and pigs. The aim of this study is to demonstrate, estimate the magnitude, and statistically model the effect of individual and herd prevalence of the infection on milk and meat production, lifespan, health status and mortality of the individuals.
Commercially available tests for diagnosing diseases are not perfect, and their sensitivity and specificity are often considerably less than 100%. True prevalence can therefore be investigated primarily by complex Bayesian statistical methods.
The PhD student's task is to develop frequentist and Bayesian statistical models that can be used to examine the relationship between individual and herd prevalence, and production indicators. A further task is to extend statistical modeling to the risk of events in the life history of an individual (pregnancy, calving, culling, death) and times to events using statistical methods of survival analysis.
Required language skills: English Further requirements: Skill and practice in the application of Bayesian and frequentist methods of biostatistics; Practice in the use of the R statistical software environment; Practice in the use of the rstan package (Bayesian modeling) of the R statistical software