Evaluation of a New Strategy for Control of Bovine Tuberculosis in Michigan White-Tailed Deer: Year 1 Progress Report

The State of Michigan is striving to eliminate bovine tuberculosis (Tb) infection among free-ranging white-tailed deer in the northeastern Lower Peninsula of the state. Aggressive reduction in the overall deer population abundance may help to further reduce TB prevalence, but this course of action is unacceptable to many hunters and landowners. Targeted culling of sick deer would likely be far more acceptable to these stakeholders, so in the winter of 2003 the Michigan Department of Natural Resources pilot-trialed a new strategy based on live-trapping and Tb-testing of wild deer. The field study was conducted in a township with relatively high TB prevalence within Deer Management Unit 452 in the northeastern Lower Peninsula. Over a 2-month trapping period, 119 individual deer were live-trapped, blood sampled, fitted with a radio-collar, and released. A total of 31 of these deer were subsequently classified as Tb-suspect by at least one of five blood tests employed (however there was a low level of agreement among tests). A delay in testing meant that only six of these suspect deer were culled by sharpshooters before pre-programmed release of their radio-collars, after which they could no longer be located. Mycobacterium bovis was cultured from one of these six suspect deer; the other five were negative on culture. All target deer were located to within shooting range with 1 – 2 days of effort, and all the radio-collars on the apparently-healthy deer dropped off after the intended 90-day interval, and were thereafter recovered for re-use. There was considerable support for this pilot project among hunters, farmers, state and federal agriculture agencies, the media and the general public, and so we recommend that further field trials be undertaken using this technique. The initial focus of these trials should be on improving the efficacy and reliability of the blood testing procedure.

Improving IRT parameter estimates with small sample sizes: Evaluating the efficacy of a new data augmentation technique

The 3PL model is a flexible and widely used tool in assessment. However, it suffers from limitations due to its need for large sample sizes. This study introduces and evaluates the efficacy of a new sample size augmentation technique called Duplicate, Erase, and Replace (DupER) Augmentation through a simulation study. Data are augmented using several variations of DupER Augmentation (based on different imputation methodologies, deletion rates, and duplication rates), analyzed in BILOG-MG 3, and results are compared to those obtained from analyzing the raw data. Additional manipulated variables include test length and sample size. Estimates are compared using seven different evaluative criteria. Results are mixed and inconclusive. DupER augmented data tend to result in larger root mean squared errors (RMSEs) and lower correlations between estimates and parameters for both item and ability parameters. However, some DupER variations produce estimates that are much less biased than those obtained from the raw data alone. For one DupER variation, it was found that DupER produced better results for low-ability simulees and worse results for those with high abilities. Findings, limitations, and recommendations for future studies are discussed. Specific recommendations for future studies include the application of Duper Augmentation (1) to empirical data, (2) with additional IRT models, and (3) the analysis of the efficacy of the procedure for different item and ability parameter distributions.