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Confidence interval for a linear contrast of standardized mean differences from 2-group studies

Source: R/meta_comp.R
meta.lc.stdmean2.Rd

Computes the estimate, standard error, and confidence interval for a linear contrast of 2-group standardized mean differences from two or more studies. Equality of variances within or across studies is not assumed. Use the square root average variance standardizer (stdzr = 0) for 2-group experimental designs. Use the square root weighted variance standardizer (stdzr = 3) for 2-group nonexperimental designs with simple random sampling. The stdzr = 1 and stdzr = 2 options can be used with either experimental or nonexperimental designs.

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

Usage

meta.lc.stdmean2(alpha, m1, m2, sd1, sd2, n1, n2, v, stdzr)

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

stdzr

  • set to 0 for square root unweighted average variance standardizer

  • set to 1 for group 1 SD standardizer

  • set to 2 for group 2 SD standardizer

  • set to 3 for square root weighted average variance 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(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.stdmean2(.05, m1, m2, sd1, sd2, n1, n2, v, 0)
#>          Estimate      SE     LL     UL
#> Contrast   0.8558 0.27092 0.3248 1.3868

# Should return: 
#          Estimate      SE     LL     UL
# Contrast   0.8558 0.27092 0.3248 1.3868