Sample Size Estimation in Research With Dependent Measures and Dichotomous Outcomes is a research paper published in American Journal of Public Health (2004). On theSindex it has a DataRank of 1.2. It has been cited 23 times, with 23 citing works in its 1-hop citation network.
I reviewed sample estimation methods for research designs involving nonindependent data and a dichotomous response variable to examine the importance of proper sample size estimation and the need to align methods of sample size estimation with planned methods of statistical analysis. Examples and references to published literature are provided in this article. When the method of sample size estimation is not in concert with the method of planned analysis, poor estimates may result. The effects of multiple measures over time also need to be considered. Proper sample size estimation is often overlooked. Alignment of the sample size estimation method with the planned analysis method, especially in studies involving nonindependent data, will produce appropriate estimates.
FAIR checklist signals are shown for context only and do not affect DataRank scoring.
Base Score Contribution
0.477
From this paper's citation signal
Citation Network Contribution
0.727
From 16 citing papers with measurable signal
Ranked by citation count — the same ordering the engine uses when summing log1p(Cq) over citers.
DataRank blends this paper's own citation count with the influence of the papers that cite it. Here, roughly 40% comes from its base citations and 60% from the citation network (16 citing papers contributed measurable signal).
Citers are pulled from OpenAlex sorted by cited_by_count:descand capped per paper, so when the cap binds we keep the highest-signal references and the score is reproducible across reruns.
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