Computes confidence intervals for a population standardized mean difference in a paired-samples design. A square root unweighted variance standardizer and single measurement standard deviation standardizers are used. Equality of variances is not assumed.

ci.stdmean.ps(alpha, m1, m2, sd1, sd2, cor, n)

Arguments

alpha

alpha level for 1-alpha confidence

m1

estimated mean of measurement 1

m2

estimated mean of measurement 2

sd1

estimated standard deviation of measurement 1

sd2

estimated standard deviation of measurement 2

cor

estimated correlation between measurements

n

sample size

Value

Returns a 3-row matrix. The columns are:

  • Estimate - bias adjusted standardized mean difference

  • SE - standard error

  • LL - lower limit of the confidence interval

  • UL - upper limit of the confidence interval

References

Bonett DG (2008). “Confidence intervals for standardized linear contrasts of means.” Psychological Methods, 13(2), 99--109. ISSN 1939-1463, doi:10.1037/1082-989X.13.2.99 .

Examples

ci.stdmean.ps(.05, 110.4, 102.1, 15.3, 14.6, .75, 25)
#>                              Estimate        SE        LL        UL
#> Unweighted standardizer:    0.5433457 0.1609934 0.2394905 0.8705732
#> Measurement 1 standardizer: 0.5253526 0.1615500 0.2258515 0.8591158
#> Measurement 2 standardizer: 0.5505407 0.1692955 0.2366800 0.9003063

# Should return:
#                              Estimate        SE        LL        UL
# Unweighted standardizer:     0.5433457 0.1609934 0.2394905 0.8705732
# Measurement 1 standardizer:  0.5253526 0.1615500 0.2258515 0.8591158
# Measurement 2 standardizer:  0.5505407 0.1692955 0.2366800 0.9003063