Diagnostic tests play a crucial role in medical care. Thus any new diagnostic tests must undergo a thorough evaluation. New diagnostic tests are evaluated in comparison with the respective gold standard tests. The performance of binary diagnostic tests is quantified by accuracy measures, with sensitivity and specificity being the most important measures. In any diagnostic accuracy study, the estimates of these measures are often biased owing to selective verification of the patients, which is referred to as partial verification bias. Several methods for correcting partial verification bias are available depending on the scale of the index test, target outcome, and missing data mechanism. However, these are not easily accessible to the researchers due to the complexity of the methods. This article aims to provide a brief overview of the methods available to correct for partial verification bias involving a binary diagnostic test and provide a practical tutorial on how to implement the methods using the statistical programming language R.
A new method for estimating the time to colonization of Methicillin-resistant Staphylococcus Aureus (MRSA) patients is developed in this paper. The time to colonization of MRSA is modelled using a Bayesian smoothing approach for the hazard function. There are two prior models discussed in this paper: the first difference prior and the second difference prior. The second difference prior model gives smoother estimates of the hazard functions and, when applied to data from an intensive care unit (ICU), clearly shows increasing hazard up to day 13, then a decreasing hazard. The results clearly demonstrate that the hazard is not constant and provide a useful quantification of the effect of length of stay on the risk of MRSA colonization which provides useful insight.
To assess the public health importance of malaria on Banggi Island, Sabah, baseline epidemiological and entomological data were obtained in a study of three villages. These data were used to model the transmission of malaria using a non-seasonal version of the deterministic model of Dietz, Molineaux and Thomas. The model provided a satisfactory description of prevalence rates of Plasmodium falciparum parasitaemia. Modifications to the basic model enable the effects of mass chemotherapy with various combinations of schizonticidal and gametocidal drugs to be simulated. In this way, the relative merits of different procedures of mass drug administration can be compared. The fitted model is also used to examine the relationship between the overall prevalence of infection and the vectorial capacity, and to predict the consequences of a reduction in the size of the vector population.