| meta.ave.meanratio.ps {vcmeta} | R Documentation |
Confidence interval for an average mean ratio from paired-samples studies
Description
Computes the estimate, standard error, and confidence interval for a geometric average mean ratio from two or more paired-samples studies. A Satterthwaite adjustment to the degrees of freedom is used to improve the accuracy of the confidence interval for the average effect size. Equality of variances within or across studies is not assumed.
Usage
meta.ave.meanratio.ps(alpha, m1, m2, sd1, sd2, cor, n, bystudy = TRUE)
Arguments
alpha |
alpha level for 1-alpha confidence |
m1 |
vector of estimated means for measurement 1 |
m2 |
vector of estimated means for measurement 2 |
sd1 |
vector of estimated SDs for measurement 1 |
sd2 |
vector of estimated SDs for measurement 2 |
cor |
vector of estimated correlations for paired measurements |
n |
vector of sample sizes |
bystudy |
logical to also return each study estimate (TRUE) or not |
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 effect size
SE - standard error
LL - lower limit of the confidence interval
UL - upper limit of the confidence interval
exp(Estimate) - exponentiated estimate
exp(LL) - lower limit of the exponentiated confidence interval
exp(UL) - upper limit of the exponentiated confidence interval
df - degrees of freedom
Examples
m1 <- c(53, 60, 53, 57)
m2 <- c(55, 62, 58, 61)
sd1 <- c(4.1, 4.2, 4.5, 4.0)
sd2 <- c(4.2, 4.7, 4.9, 4.8)
cor <- c(.7, .7, .8, .85)
n <- c(30, 50, 30, 70)
meta.ave.meanratio.ps(.05, m1, m2, sd1, sd2, cor, n, bystudy = TRUE)
# Should return:
# Estimate SE LL UL
# Average -0.05695120 0.004350863 -0.06558008 -0.04832231
# Study 1 -0.03704127 0.010871086 -0.05927514 -0.01480740
# Study 2 -0.03278982 0.008021952 -0.04891054 -0.01666911
# Study 3 -0.09015110 0.009779919 -0.11015328 -0.07014892
# Study 4 -0.06782260 0.004970015 -0.07773750 -0.05790769
# exp(Estimate) exp(LL) exp(UL) df
# Average 0.9446402 0.9365240 0.9528266 103.0256
# Study 1 0.9636364 0.9424474 0.9853017 29.0000
# Study 2 0.9677419 0.9522663 0.9834691 49.0000
# Study 3 0.9137931 0.8956968 0.9322550 29.0000
# Study 4 0.9344262 0.9252073 0.9437371 69.0000