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. Use the t.test function for raw data input.

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 - 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.

Examples

ci.mean2(.05, 15.4, 10.3, 2.67, 2.15, 30, 20)
#>                              Estimate        SE        t       df            p
#> Equal Variances Assumed:          5.1 0.7151214 7.131656 48.00000 4.621279e-09
#> Equal Variances Not Assumed:      5.1 0.6846568 7.448987 46.17476 1.898214e-09
#>                                    LL       UL
#> Equal Variances Assumed:     3.662152 6.537848
#> Equal Variances Not Assumed: 3.721998 6.478002

# Should return:
#                              Estimate       SE        t      df      
# Equal Variances Assumed:          5.1 1.602248 3.183029 48.0000 
# Equal Variances Not Assumed:      5.1 1.406801 3.625247 44.1137 
#                                          p       LL       UL
# Equal Variances Assumed:      0.0025578586 1.878465 8.321535
# Equal Variances Not Assumed:  0.0007438065 2.264986 7.935014