Il 05/09/2019 00:00, r-sig-meta-analysis-request at r-project.org ha scritto:
...................... .......................... This isn't built into metafor. But the computations are easy to carry out 'by hand'. Let's say you have data like this: dat <- data.frame(study = 1:4, ni = c(32, 10, 14, 7), hits = c(14, 3, 0, 6), ki = c(4, 6, 5, 4)) which is actually Table 5 in the paper. Then we can compute this outcome measure and the corresponding sampling variances with: dat$Pi <- with(dat, ifelse(hits == 0, 0.5 / (ni + 1), hits / ni)) dat$yi <- with(dat, Pi*(ki-1) / (1 + Pi*(ki-2))) dat$vi <- with(dat, 1/ni * yi^2*(1-yi)^2 / (Pi*(1-Pi))) dat
Thank you for this implementation in metafor, however a trick of this effect size is that values above .5 are related to a positive effect (hits above chance) and viceversa. Running a fixed or random model? in metafor, all values are considered as positive. Do I have to calculate the dat$yi subtracting .5? And if this adjustment is correct, the calculation of dat$vi remains the same? Patrizio -- Patrizio E. Tressoldi Ph.D. Dipartimento di Psicologia Generale Universit? di Padova via Venezia 8 35131 Padova - ITALY http://www.patriziotressoldi.it https://orcid.org/0000-0002-6404-0058 Science of Consciousness Research Group http://dpg.unipd.it/en/soc Make war history support https://en.emergency.it