Confidence interval for a linear contrast of mean differences from paired-samples studies
Source: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.
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
- v
vector of contrast coefficients
Value
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
References
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 .
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(.72, .78, .81, .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 0.4681205 1.57207 3.42793 107.657
# Should return:
# Estimate SE LL UL df
# Contrast 2.5 0.4681205 1.57207 3.42793 107.657