PubMed · 7732108
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J A Heermann, M E Megel. 1994. Data analysis.. https://pubmed.ncbi.nlm.nih.gov/7732108/
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The authors propose a method for adjusting results of log-linear multi-source capture-recapture estimates of total population. The method compares the totals in some subpopulations of known size with estimates derived from various capture-recapture approaches to these subpopulations. The authors term such an approach an "internal validity analysis". Trends in the ratios of the estimates to the known true values of these subpopulations provide a plausible indicator of the bias of some types of estimates of the total population especially when underlying assumptions of the methods used have not been met in analysis of the total population. The authors apply this method to published data on an open population of injection drug users that had been previously analyzed with a standard capture-recapture analysis as if it were a closed population. Internal validity analysis suggests that the size of this population is about 15% greater than that previously estimated.
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Sample size calculations are now mandatory for many research protocols, but the ones useful in common situations are not all easily accessible. This paper outlines the ways of calculating sample sizes in two group studies for binary, ordered categorical, and continuous outcomes. Formulas and worked examples are given. Maximum power is usually achieved by having equal numbers in the two groups. However, this is not always possible and calculations for unequal group sizes are given.