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Examining war exposure (The Russian invasion in Ukraine) in Romanian adolescents

Summary We compare two binary diagnostic tests when each subject is measured more than once with each test and with a gold standard. We introduce a new model that allows the correlation between two measurements on a single subject by the same test to be different from the correlation between two measurements by different tests. We show that moment estimators of the population parameters for the mean sensitivities and specificities are virtually identical to the maximum likelihood estimates from our random-effects model. We apply the model to data comparing two rapid malaria tests and provide guidance for choosing the number of subjects and repeated measurements.

This discussion focuses on on the assessment of a single binary measurement system in a specific context that is commonly found in the manufacturing industry

Binary measurement systems that classify parts as pass or fail are widely used in industry, especially for systematic inspection in high-volume processes. In this context, we are likely to have available a large number of previously measured passed and failed parts. To support production and quality improvement, it is important to assess the misclassification rates, e.g., the probability of failing a conforming part or passing a nonconforming part. We may also want to estimate the unknown conforming rate. Here we focus on the assessment of a binary measurement system when no gold-standard measurement system is available. The standard assessment plan is to repeatedly measure a sample of parts and use a latent class model. We demonstrate the substantial benefit of supplementing the standard plan with the available data from the previously measured parts. We propose new sampling plans and compare them with the standard plan with respect to the precision of the estimators of the misclassification rates. We also give recommendations for planning an assessment study when we can sample from a population of previously measured parts.

Despite the widespread use of binary measurement systems, little has been written about assessing them. Two plans are proposed here for assessing binary measurement systems that may be used under the assumption that the pass rate of the system is known..

This research was supported by grants from the Natural Sciences and Engineering Research Council of Canada.

Background Although multiple studies have estimated the prevalence of neurological conditions in the general Canadian population, limited research exists regarding the proportion affected with these conditions in non-acute health care settings in Canada. Data from standardized clinical assessments based on the interRAI suite of instruments were used to estimate the prevalence of eight neurological conditions across the continuum of care including Alzheimer’s disease, Parkinson’s disease, epilepsy, traumatic brain injury, multiple sclerosis, cerebral palsy, Huntington’s disease, and amyotrophic lateral sclerosis. Methods Cohorts of individuals receiving care in nursing homes (N=103,820), home care (N=91,021), complex continuing care (N=10,581), and psychiatric hospitals (N=23,119) in Canada were drawn based on their most recent interRAI assessment within each sector for a six-month period in 2010. These data were linked to the Discharge Abstract Database and National Ambulatory Care Reporting System data sets to develop five different case definition scenarios for estimating prevalence. Results The conditions with the highest estimated prevalences in these care settings in Canada were Alzheimer’s disease and related dementias, Parkinson’s disease, epilepsy, and traumatic brain injury. However, there were notable cross-sector differences in the prevalence of each condition, and regional variations. Prevalence estimates based on acute hospital administrative data alone were substantially lower for all conditions evaluated. Conclusions The proportion of persons with neurological conditions in non-acute health care settings in Canada is substantially higher than is generally reported for the general population. It is essential for these care settings to have the expertise and resources to respond effectively to the strengths, preferences, and needs of the growing population of persons with neurological conditions. The use of hospital or emergency department records alone is likely to substantially underestimate the true prevalence of neurological conditions across the continuum of care. However, interRAI assessment records provide a helpful source of information for obtaining these estimates in nursing home, home care, and mental health settings.