Exponentiated confidence interval for an average of log-transformed parameters
Source:R/meta_ave.R
meta.ave.gen.log.Rd
Computes the estimate, standard error, and confidence interval for an average of any type of log-transformed parameter (e.g., log mean ratio, log proportion ratio, log odds ratio) from two or more studies.
Value
Returns a matrix. The first row is the average estimate across all studies. If bystudy is TRUE, there is 1 additional row for each study. The matrix has the following columns:
Estimate - estimated log effect size (from input)
SE - standard error of log effect size (from input)
LL - lower limit of the confidence interval
UL - upper limit of the confidence interval
exp(Estimate) - exponentiated estimate
LL - lower limit of the exponentiated confidence interval
UL - upper limit of the exponentiated confidence interval
Examples
est <- c(.165, .193, .218)
se <- c(.0684, .0921, .0882)
meta.ave.gen.log(.05, est, se, bystudy = TRUE)
#> Estimate SE LL UL exp(Estimate) exp(LL)
#> Average 0.192 0.04823578 0.09745962 0.2865404 1.211671 1.102367
#> Study 1 0.165 0.06840000 0.03093846 0.2990615 1.179393 1.031422
#> Study 2 0.193 0.09210000 0.01248732 0.3735127 1.212883 1.012566
#> Study 3 0.218 0.08820000 0.04513118 0.3908688 1.243587 1.046165
#> exp(UL)
#> Average 1.331812
#> Study 1 1.348593
#> Study 2 1.452829
#> Study 3 1.478265
# Should return:
# Estimate SE LL UL exp(Estimate)
# Average 0.192 0.04823578 0.09745962 0.2865404 1.211671
# Study 1 0.165 0.06840000 0.03093846 0.2990615 1.179393
# Study 2 0.193 0.09210000 0.01248732 0.3735127 1.212883
# Study 3 0.218 0.08820000 0.04513118 0.3908688 1.243587
# exp(LL) exp(UL)
# Average 1.102367 1.331812
# Study 1 1.031422 1.348593
# Study 2 1.012566 1.452829
# Study 3 1.046165 1.478265