Abstract
One of the key measurements in any quantitative study, the effect size (ES) is scarce in research into astrology. Often it is unreported, unknown or unknowable. When the ES is listed, it is in terms that are hard to compare with other studies. In a quest for a simple universal ES, six methods are reviewed. Cohen’s kappa is rejected due to serious issues in favour of a formula for calculating Pearson’s r from the p-value and sample size from Professors Rosenthal and DiMatteo (2001). This ES equation is used to address the criticism that astrology studies have a very weak effect. This judgement is refuted by a meta-analysis of ten recent results in natal astrology (published in Correlation in 2020 and 2021). The resulting mean and median of the ES (M: r =.24; Mdn r = .21) affirm that outcomes tend to cluster in the small to medium range. However, there is a trend for univariate (single factor) tests to yield a small effect size. Multivariate results (two or more factors) tend to lie in the medium range and ‘Whole Chart’ experiments (all  available factors) tend to fall in the medium to high effect size category. Using a power analysis of the ES of these results, minimum sample sizes for future studies are calculated according to the type of test.