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Currently there seem to be very few sample size calculations or recommendations for developing or validating multivariable models which are based on the prognostic ability of a model, rather than the significance of its coefficients.
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As for α-adducin gene G460T, we identified 23 eligible reports published both in Chinese (n = 20) and English (n = 4), which met our inclusion/exclusion criteria, whereas due to the shared study groups, we removed five of them with the fewer sample sizes.
Prognostic studies of time-to-event data, where researchers aim to develop or validate multivariable prognostic models in order to predict survival, are commonly seen in the medical literature; however, most are performed retrospectively and few consider sample size prior to analysis.
A minimum of 5 animals per group were used, in treatments inducing fewer tumours sample size was increased to 10.
All but Puffer et al. [ 10] reported that very few trials had sample size calculations which included clustering and about half took clustering into account in the analysis, fewer in the African studies reported by Isaakidis and Ioannidis.
This study is one of few with sufficient sample size to accurately estimate the relationship between DME and cardiovascular outcomes.
Many studies on this topic used convenient sampling method [ 17] with very few studies of sample size over 1,000 on Chinese female adolescents.
We also agree with the point that the number of studies is few and total sample size in in vitro studies is smaller.
A few small studies (sample size <30) measured insulin and glucose as well as insulin response to any lactation, and results are consistent with our findings.
When there are few subpopulations, small sample size, and large overlap in value means, linear mixed-effects models, which take subpopulation effects into account, are numerically equivalent to the simpler generalized least-squares method.
Very few studies, however, report sample size calculations or even the information needed to accurately calculate sample sizes for grants and future research.
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