lifty.gere at gmx.de
2011-Aug-23 10:04 UTC
[R] Fisher transformation for pooling estimates - p values > 1
Dear all, I am using Fisher r to z transformation for pooling partial correlation estimates over multiple imputed data (number of imputations = 200). The number of observations in my data is 190. Unfortunately, when i calculate p values for the pooled estimates, some of them are p > 1 (ranging from 0 to 2). Here is the syntax I use. Can anybody help me find the error? nobs <- dim(my_data)[1] z <- log((1 + pcor)/(1 - pcor))/2 var_z <- rep(1/sqrt(nobs - 3), 200) combine_z <- MIcombine(results=as.list(z), variances=var_z, call=sys.call()) pcor_pooled <- (exp(2*as.numeric(combine_z[1])) - 1)/ (exp(2*as.numeric(combine_z[1])) + 1) # Calculate the upper and lower bounds z_lower <- as.numeric(combine_z[1]) - qnorm(.975)*as.numeric(combine_z[2]) z_upper <- as.numeric(combine_z[1]) + qnorm(.975)*as.numeric(combine_z[2]) pcor_lower <- (exp(2*z_lower) - 1)/(exp(2*z_lower) + 1) pcor_upper <- (exp(2*z_upper) - 1)/(exp(2*z_upper) + 1) # Calculate the P-Value pcor_p <- - as.numeric(combine_z[1])/as.numeric(combine_z[2]) pcor_pvalue <- 2*pnorm(-pcor_p) Thank you! Tina --