RT Journal Article
SR Electronic
T1 Meta-analysis of the variance ratio
JF bioRxiv
FD Cold Spring Harbor Laboratory
SP 104695
DO 10.1101/104695
A1 Nicolas Traut
YR 2017
UL http://biorxiv.org/content/early/2017/01/31/104695.abstract
AB The most commonly used effect size when using meta-analysis to compare a measurement of interest in two different populations is the standardised mean difference. This is the mean difference of the measurement divided by the pooled standard deviation in the two groups. The standard deviation is usually supposed to be the same for both groups, although this assumption is often made without any particular evidence. It is possible, however, that the difference of the measurement in the two populations resides precisely in their standard deviations. This could be the case, for example, if a population of patients exhibited more "abnormal" values than a control population − both large and small − even if the mean values were the same. Fisher's test of equality of variance is designed to compare standard deviations. A variance ratio is a Fisher's ratio and Fisher distribution can be used to give confidence intervals to the estimate for one study. However, confidence interval for one study can be very wide if the study does not contain enough subjects. Here we present an approach to combine variance ratios of different studies in a meta-analytic way which produces more robust estimates under these circumstances.