ci.stdmean.strat {statpsych} | R Documentation |
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.
ci.stdmean.strat(alpha, m1, m2, sd1, sd2, n1, n2, p1)
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 |
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
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.
ci.stdmean.strat(.05, 30.2, 30.8, 10.5, 11.2, 200, 200, .533) # Should return: # Estimate SE LL UL # Weighted standardizer: -0.05528428 0.10023259 -0.2518410 0.1410636 # Group 1 standardizer: -0.05692722 0.10368609 -0.2603639 0.1460782 # Group 2 standardizer: -0.05692722 0.09720571 -0.2440911 0.1369483