R/meta_comp.R
meta.lc.mean.ps.Rd
Computes the estimate, standard error, and confidence interval for a linear contrast of paired-samples mean differences from two or more studies. A Satterthwaite adjustment to the degrees of freedom is used to improve the accuracy of the confidence interval. Equality of variances within or across studies is not assumed.
meta.lc.mean.ps(alpha, m1, m2, sd1, sd2, cor, n, v)
alpha level for 1-alpha confidence
vector of estimated means for measurement 1
vector of estimated means for measurement 2
vector of estimated SDs for measurement 1
vector of estimated SDs for measurement 2
vector of estimated correlations for paired measurements
vector of sample sizes
vector of contrast coefficients
Returns 1-row matrix with the following columns:
Estimate - estimated linear contrast
SE - standard error
LL - lower limit of the confidence interval
UL - upper limit of the confidence interval
df - degrees of freedom
Bonett DG (2009). “Meta-analytic interval estimation for standardized and unstandardized mean differences.” Psychological Methods, 14(3), 225--238. ISSN 1939-1463, doi:10.1037/a0016619 .
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)
v <- c(.5, .5, -.5, -.5)
meta.lc.mean.ps(.05, m1, m2, sd1, sd2, cor, n, v)
#> Estimate SE LL UL df
#> Contrast 2.5 0.4943114 1.520618 3.479382 112.347
# Should return:
# Estimate SE LL UL df
# Contrast 2.5 0.4943114 1.520618 3.479382 112.347