Biomedical subjects
Publications and source records attributed to S Lemeshow.
Relative excess risk due to interaction, the proportion of disease among those with both exposures that is attributable to their interaction, and the synergy index have been proposed as measures of interaction in epidemiologic studies. This paper presents the methodology for obtaining confidence interval estimates of these indices utilizing routinely available output from multiple logistic regression software.
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BACKGROUND: There is considerable evidence that members of managed care organizations use fewer hospital resources than patients covered by traditional health insurance. While intensive care might seem to be an unlikely setting for such differences to exist, the relationship between health coverage and use of intensive care has not been examined. METHODS: We conducted a cross-sectional analysis of consecutive intensive care unit admissions at a regional tertiary care teaching hospital. Patients in managed care plans (n = 159) and with traditional insurance (n = 389) were compared with respect to length of stay, hospital charges, charges for specific services, and use of mechanical ventilation. The analysis controlled for severity of illness, as measured by the Mortality Probability Model, case mix, and mortality. The whole sample as well as subsamples representing medical, emergency surgery, and elective surgery patients were examined. RESULTS: The managed care group, on average, had short stays (both hospital and intensive care unit), lower charges, and less use of mechanical ventilation than the traditionally insured group. Average differences of about 30% to 40% were observed. The finding held for the whole sample as well as the medical and emergency surgery subsamples. The differences were more pronounced in the patients with lowest severity of illness. CONCLUSION: Even in a setting where there would appear to be relatively little room for discretion in treatment decisions, incentives associated with type of health insurance seemed to affect resource use.
A Monte Carlo model simulating actual populations was employed to evaluate the precision in estimation of a standardized sampling method proposed by the Global Programme on AIDS of the World Health Organization, for general use in collecting population-based data on HIV seroprevalence. It appears that in real populations, where there is likely to be 'pocketing' of infection, the proposed methodology will generally fail to provide estimates accurate to within 1% of the true population value. However, if the primary objective of a particular survey is to construct confidence intervals that include the true population HIV seroprevalence rate, then this survey method appears to be a reasonable choice. This study also suggests that selection of only one adult per household improves the precision of resulting estimates. However, since selection of only one adult per household would require that more households be visited, any gain in precision would need to be weighed against the likely increase in cost of household visits.
BACKGROUND: The logistic regression model is being used with increasing frequency in all areas of public health research. In the calendar year 1989, over 30% of the articles published in the American Journal of Public Health employed some form of logistic regression modeling. In spite of this increase, there has been no commensurate increase in the use of commonly available methods for assessing model adequacy. METHODS: We review the current status of the use of logistic regression modeling in the American Journal of Public Health. We present a brief overview of currently available and easily used methods for assessing the adequacy of a fitted logistic regression model. RESULTS: An example is used to demonstrate the methods as well as a few of the adverse consequences of failing to assess the fit of the model. One important adverse consequence illustrated in the example is the inclusion of variables in the model as a result of the influence of one subject. CONCLUSIONS: Failure to address model adequacy may lead to misleading or incorrect inferences. Recommendations are made for the use of methods for assessing model adequacy and for future editorial policy in regard to the review of articles using logistic regression.
A computer program has been written which performs a stepwise selection of variables for logistic regression using maximum likelihood estimation. The selection procedure is based on likelihood ratio tests for the coefficients. These tests are used in a forward selection and a backward elimination at each step. The use of the program is illustrated by several examples.
Understanding the phenomenon of heavy smoking among women and factors related to it is of considerable public health importance. Whereas lighter smokers have been more successful in their cessation attempts, the percentage of smokers who smoke more than 25 cigarettes per day has increased in recent years. This article examines the hypothesis that, compared to lighter smokers, female heavy smokers will report more responsiveness to internal cues to smoke, less interest in quitting, more difficulty with previous cessation attempts, more uncertainty about cessation strategies, and more concern about weight gain as a result of quitting. We collected data in 1984 through a self-administered survey completed by 874 women employed as nurses in acute care, chronic care, and home care nursing in Worcester, Massachusetts; we base our analyses on data collected from 158 light and moderate smokers and 67 heavy smokers. Our findings suggest that, compared to lighter smokers, heavy smokers may depend more on nicotine and are likely to respond to a broader array of cues to smoke, factors that appear to contribute to heavy smokers' greater difficulties with quitting. These female heavy smokers are just as likely as lighter smokers to have made previous attempts to quit and want to quit just as much. Major barriers to quitting for female heavy smokers include a lack of confidence in their ability to quit, insufficient tools to succeed with cessation attempts, and fear that weight gain will accompany quitting.