Confidence interval for an average mean difference from 2-group studies
Source:R/meta_ave.R
meta.ave.mean2.Rd
Computes the estimate, standard error, and confidence interval for an average mean difference from two or more 2-group studies. A Satterthwaite adjustment to the degrees of freedom is used to improve the accuracy of the confidence intervals. 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
- 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
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(7.4, 6.9)
m2 <- c(6.3, 5.7)
sd1 <- c(1.72, 1.53)
sd2 <- c(2.35, 2.04)
n1 <- c(40, 60)
n2 <- c(40, 60)
meta.ave.mean2(.05, m1, m2, sd1, sd2, n1, n2, bystudy = TRUE)
#> Estimate SE LL UL df
#> Average 1.15 0.2830183 0.5904369 1.709563 139.41053
#> Study 1 1.10 0.4604590 0.1819748 2.018025 71.46729
#> Study 2 1.20 0.3292036 0.5475574 1.852443 109.42136
# Should return:
# Estimate SE LL UL df
# Average 1.15 0.2830183 0.5904369 1.709563 139.41053
# Study 1 1.10 0.4604590 0.1819748 2.018025 71.46729
# Study 2 1.20 0.3292036 0.5475574 1.852443 109.42136