The findings of this study indicate that there are substantial discrepancies between self-reported and administrative data among older adults. Researchers seeking to examine health-care use among older adults need to consider these discrepancies in the interpretation of their results. Failure to recognize these discrepancies between survey and administrative data among older adults may lead to the establishment of inappropriate health-care policies.
Latent class models can be used to assess diagnostic test performance when there is no perfectly accurate gold standard test available for comparison. These models usually assume independent errors between the tests, conditional on the true disease state of the subject. Maximum likelihood estimates of the prevalence of the disease and the error rates of diagnostic tests are then obtained. This paper examines the impact of error dependencies between binary diagnostic tests on the parameter estimates obtained from the latent class models. The independence model often gives parameter estimates having relatively small bias, but in some situations (for example, when disease prevalence is low and the tests have low specificity, such as in population screening) the bias may be more serious.
Background: Standardized mortality ratios are used to identify geographic areas with higher or lower mortality than expected. This article examines geographic disparity in premature mortality in Ontario, Canada, at three geographic levels of population and considers factors that may underlie variations in premature mortality across geographic areas. All-cause, sex and disease chapter specific premature mortality were analyzed at the regional, district and public health unit level to determine the extent of geographic variation. Standardized mortality ratios for persons aged 0-74 years were calculated to identify geographic areas with significantly higher or lower premature mortality than expected, using Ontario death rates as the basis for the calculation of expected deaths in the local population. Data are also presented from the household component of the 1996/ 97 National Population Health Survey and from the 1996 Statistics Canada Census.
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