ci.stdmean.strat {statpsych}

Confidence interval for a 2-group standardized mean difference with stratified sampling

Description

Computes confidence intervals for a population standardized mean difference in a 2-group nonexperimental design with stratified random sampling (a random sample of a specificied size from each subpopulation) using a square root weighted variance standardizer or single group standard deviation standardizer. Equality of variances is not assumed.

Usage

ci.stdmean.strat(alpha, m1, m2, sd1, sd2, n1, n2, p1)

Arguments

alpha

alpha level for 1-alpha confidence

m1

estimated mean for group 1

m2

estimated mean for group 2

sd1

estimated standard deviation for group 1

sd2

estimated standard deviation for group 2

n1

sample size for group 1

n2

sample size for group 2

p1

proportion of total population in subpopulation 1

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 (2020). “Point-biserial correlation: Interval estimation, hypothesis testing, meta-analysis, and sample size determination.” British Journal of Mathematical and Statistical Psychology, 73(S1), 113–144. ISSN 0007-1102, doi:10.1111/bmsp.12189.

Examples

ci.stdmean.strat(.05, 33.2, 30.8, 10.5, 11.2, 200, 200, .533)

# Should return:
#                         Estimate  adj Estimate         SE         LL        UL
# Weighted standardizer: 0.2215549     0.2211371 0.10052057 0.02453817 0.4185716
# Group 1 standardizer:  0.2285714     0.2277089 0.10427785 0.02419059 0.4329523
# Group 2 standardizer:  0.2142857     0.2277089 0.09776049 0.02267868 0.4058927