Confidence interval for a linear contrast of mean differences from 2-group studies
Source:R/meta_comp.R
meta.lc.mean2.Rd
Computes the estimate, standard error, and confidence interval for a linear contrast of 2-group 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 group 1
- m2
vector of estimated means for group 2
- sd1
vector of estimated SDs for group 1
- sd2
vector of estimated SDs for group 2
- n1
vector of group 1 sample sizes
- n2
vector of group 2 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(45.1, 39.2, 36.3, 34.5)
m2 <- c(30.0, 35.1, 35.3, 36.2)
sd1 <- c(10.7, 10.5, 9.4, 11.5)
sd2 <- c(12.3, 12.0, 10.4, 9.6)
n1 <- c(40, 20, 50, 25)
n2 <- c(40, 20, 48, 26)
v <- c(.5, .5, -.5, -.5)
meta.lc.mean2(.05, m1, m2, sd1, sd2, n1, n2, v)
#> Estimate SE LL UL df
#> Contrast 9.95 2.837787 4.343938 15.55606 153.8362
# Should return:
# Estimate SE LL UL df
# Contrast 9.95 2.837787 4.343938 15.55606 153.8362