meta.lc.mean.ps {vcmeta}

Confidence interval for a linear contrast of mean differences from paired-samples studies

Description

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.

Usage

meta.lc.mean.ps(alpha, m1, m2, sd1, sd2, cor, n, v)

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(.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)

# Should return:
#          Estimate        SE       LL       UL      df
# Contrast      2.5 0.4943114 1.520618 3.479382 112.347