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

Source: R/meta_comp.R
meta.lc.stdmean.ps.Rd

Computes the estimate, standard error, and confidence interval for a linear contrast of paired-samples standardized mean differences from two or more studies. Equality of variances within or across studies is not assumed.

For more details, see Section 3.2 of Bonett (2021, Volume 5).

Usage

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

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

stdzr

  • set to 0 for square root unweighted average variance standardizer

  • set to 1 for measurement 1 SD standardizer

  • set to 2 for measurement 2 SD standardizer

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

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 .

Bonett DG (2021). Statistical Methods for Psychologists, Vol 1-5, https://dgbonett.sites.ucsc.edu/.

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.stdmean.ps(.05, m1, m2, sd1, sd2, cor, n, v, 0)
#>          Estimate      SE     LL     UL
#> Contrast   0.5128 0.13468 0.2488 0.7767

# Should return:
#          Estimate      SE     LL     UL
# Contrast   0.5128 0.13468 0.2488 0.7767