1000 resultados para Library surveys


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Geddes Pond, 1905: Map of the Huron River Valley

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Vivienne Farm, 1907: Map of the Huron River Valley

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Fleming Creek, 1907: Map of the Huron River Valley

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Superior Pond, ca. 1906-1907: Map of the Huron River Valley

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Leforge Road, 1907: Map of the Huron River Valley

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Ypsilanti, 1907: Map of the Huron River Valley

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Ann Arbor, ca. 1905-1909: Map of the Huron River Valley, revised 5/11/1915

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Accurate monitoring of prevalence and trends in population levels of physical activity (PA) is a fundamental public health need. Test-retest reliability (repeatability) was assessed in population samples for four self-report PA measures: the Active Australia survey (AA, N=356), the short International Physical Activity Questionnaire (IPAQ, N=104), the physical activity items in the Behavioral Risk Factor Surveillance System (BRFSS, N=127) and in the Australian National Health Survey (NHS, N=122). Percent agreement and Kappa statistics were used to assess reliability of classification of activity status as 'active', 'insufficiently active' or 'sedentary'. Intraclass correlations (ICCs) were used to assess agreement on minutes of activity reported for each item of each survey and for total minutes. Percent agreement scores for activity status were very good on all four instruments, ranging from 60% for the NHS to 79% for the IPAQ. Corresponding Kappa statistics ranged from 0.40 (NHS) to 0.52 (AA). For individual items, ICCs were highest for walking (0.45 to 0.78) and vigorous activity (0.22 to 0.64) and lowest for the moderate questions (0.16 to 0.44). All four measures provide acceptable levels of test-retest reliability for assessing both activity status and sedentariness, and moderate reliability for assessing total minutes of activity.

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The use of presence/absence data in wildlife management and biological surveys is widespread. There is a growing interest in quantifying the sources of error associated with these data. We show that false-negative errors (failure to record a species when in fact it is present) can have a significant impact on statistical estimation of habitat models using simulated data. Then we introduce an extension of logistic modeling, the zero-inflated binomial (ZIB) model that permits the estimation of the rate of false-negative errors and the correction of estimates of the probability of occurrence for false-negative errors by using repeated. visits to the same site. Our simulations show that even relatively low rates of false negatives bias statistical estimates of habitat effects. The method with three repeated visits eliminates the bias, but estimates are relatively imprecise. Six repeated visits improve precision of estimates to levels comparable to that achieved with conventional statistics in the absence of false-negative errors In general, when error rates are less than or equal to50% greater efficiency is gained by adding more sites, whereas when error rates are >50% it is better to increase the number of repeated visits. We highlight the flexibility of the method with three case studies, clearly demonstrating the effect of false-negative errors for a range of commonly used survey methods.

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Skin cancers pose a significant public health problem in high-risk populations. We have prospectively monitored basal cell carcinoma (BCC) and squamous cell carcinoma (SCC) incidence in a Queensland community over a 10-y period by recording newly treated lesions, supplemented by skin examination surveys. Age-standardized incidence rates of people with new histologically confirmed BCC were 2787 per 100,000 person-years at risk (pyar) among men and 1567 per 100,000 pyar among women, and corresponding tumor rates were 5821 per 100,000 pyar and 2733 per 100,000 pyar, respectively. Incidence rates for men with new SCC were 944 per 100,000 pyar and for women 675 per 100,000 pyar; tumor rates were 1754 per 100,000 pyar and 846 per 100,000 pyar, respectively. Incidence rates of BCC tumors but not SCC tumors varied noticeably according to method of surveillance, with BCC incidence rates based on skin examination surveys around three times higher than background treatment rates. This was mostly due to an increase in diagnosis of new BCC on sites other than the head and neck, arms, and hands associated with skin examination surveys and little to do with advancing the time of diagnosis of BCC on these sites as seen by a return to background rates following the examination surveys. We conclude that BCC that might otherwise go unreported are detected during skin examination surveys and thus that such skin cancer screening can influence the apparent burden of skin cancer.