Confidence interval for a 2-group mean difference

Computes equal variance and unequal variance confidence intervals for a population 2-group mean difference using the estimated means, estimated standard deviations, and sample sizes. Also computes equal variance and unequal variance independent-samples t-tests. Use the t.test function for raw data input.

For more details, see Section 2.3 of Bonett (2021, Volume 1)

Usage

ci.mean2(alpha, m1, m2, sd1, sd2, n1, n2)

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

Value

Returns a 2-row matrix. The columns are:

Estimate - estimated mean difference
SE - standard error
t - t test statistic
df - degrees of freedom
p - two-sided p-value
LL - lower limit of the confidence interval
UL - upper limit of the confidence interval

References

Snedecor GW, Cochran WG (1989). Statistical Methods, 8th edition. ISU University Pres, Ames, Iowa.

Bonett DG (2021). Statistical Methods for Psychologists https://dgbonett.sites.ucsc.edu/.

Examples

ci.mean2(.05, 19.4, 11.3, 2.70, 2.10, 40, 40)
#>                              Estimate        SE       t    df p       LL
#> Equal Variances Assumed:          8.1 0.5408327 14.9769 78.00 0 7.023285
#> Equal Variances Not Assumed:      8.1 0.5408327 14.9769 73.54 0 7.022255
#>                                    UL
#> Equal Variances Assumed:     9.176715
#> Equal Variances Not Assumed: 9.177745
# Should return:
#                              Estimate        SE       t    df p
# Equal Variances Assumed:          8.1 0.5408327 14.9769 78.00 0
# Equal Variances Not Assumed:      8.1 0.5408327 14.9769 73.54 0
#                                    LL       UL
# Equal Variances Assumed:     7.023285 9.176715
# Equal Variances Not Assumed: 7.022256 9.177744