Takes a meta-analysis class object of d values or correlations (classes r_as_r, d_as_d, r_as_d, and d_as_r; second-order meta-analyses are currently not supported) as an input and uses conversion formulas and Taylor series approximations to convert effect sizes and variance estimates, respectively.
convert_ma(ma_obj, ...)convert_meta(ma_obj, ...)
A meta-analysis converted to the d value metric (if ma_obj was a meta-analysis in the correlation metric) or converted to the correlation metric (if ma_obj was a meta-analysis in the d value metric).
A meta-analysis object of class r_as_r, d_as_d, r_as_d, or d_as_r
Additional arguments.
The formula used to convert correlations to d values is: d=r1p(1-p)1-r^2(sqrt(1 / (p * (1-p))) * r) / sqrt(1 - r^2)
The formula used to convert d values to correlations is: r=dd^2+1p(1-p)d / sqrt(1 / (p * (1-p)) + d^2)
To approximate the variance of correlations from the variance of d values, the function computes: var_r a_d^2var_dvar_r ~= a_d^2 * var_d where a_da_d is the first partial derivative of the d-to-r transformation with respect to d: a_d=-1[d^2p(1-p)-1]d^2+1p-p^2a_d = -1 / ((d^2 * (p - 1) * p - 1) * sqrt(d^2 + 1 / (p - p^2)))
To approximate the variance of d values from the variance of correlations, the function computes: var_d a_r^2var_rvar_d ~= a_r^2 * var_r where a_ra_r is the first partial derivative of the r-to-d transformation with respect to r: a_r=1p-p^2(1-r^2)^1.5a_r = sqrt(1 / (p - p^2)) / (1 - r^2)^1.5