Confidence intervals for a paired-samples standardized mean difference

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 for measurement 1

m2

estimated mean for measurement 2

sd1

estimated standard deviation for measurement 1

sd2

estimated standard deviation for measurement 2

cor

estimated correlation between measurements

n

sample size

Value

Returns a 3-row matrix. The columns are:

• Estimate - estimated standardized mean difference

• adj Estimate - bias adjusted standardized mean difference estimate

• 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 adj Estimate        SE        LL
#> Unweighted standardizer:    0.5550319    0.5433457 0.1609934 0.2394905
#> Measurement 1 standardizer: 0.5424837    0.5253526 0.1615500 0.2258515
#> Measurement 2 standardizer: 0.5684932    0.5505407 0.1692955 0.2366800
#>                                    UL
#> Unweighted standardizer:    0.8705732
#> Measurement 1 standardizer: 0.8591158
#> Measurement 2 standardizer: 0.9003063

# Should return:
#                              Estimate  adj Estimate        SE        LL        UL
# Unweighted standardizer:    0.5550319     0.5433457 0.1609934 0.2394905 0.8705732
# Measurement 1 standardizer: 0.5424837     0.5253526 0.1615500 0.2258515 0.8591158
# Measurement 2 standardizer: 0.5684932     0.5505407 0.1692955 0.2366800 0.9003063