Additional study inclusion criteria included sample size of at least 10 patients per comparison group (AAT versus IAT) evaluating at least one of the following outcomes: mortality, clinical success, microbiologic eradication, length of stay (hospital and intensive care unit [ICU]), or cost.
This study aims to investigate how rank probabilities obtained from a Bayesian NMA are affected by characteristics of the network, including network configuration, number of studies per comparison, individual study sample sizes, and effect sizes.
In contrast, the willingness to offer microinsurance is negatively correlated with their loan asset ratio, bad loan write-off ratio or average loan size in comparison to GNI per capita (Kwon 2010).
This study investigates how rank probabilities are affected by various factors such as unequal number of studies per comparison in the network, the sample size of individual studies, the network configuration, and effect sizes between treatments.
Because of varying number of introns per ortholog, the average intron size includes comparison of nonhomologous introns.
We present descriptive results pertaining to the reviews (number of meta-analyses and number of comparisons per review), comparisons (number of outcomes per comparison), meta-analyses (number of studies per meta-analysis) and studies (sample size of individual studies).
Second, one may argue that sample size per group is too small for valid comparisons.
Blocking is used to ensure that comparison groups are of approximately the same size per home.
