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For a 2-group experimental design, this function computes a prediction interval for how the response variable score for one randomly selected person from the study population would differ under the two treatment conditions. Both equal variance and unequal variance prediction intervals are computed.

For more details, see Section 2.6 of Bonett (2021, Volume 1)

Usage

pi.score2(alpha, m1, m2, sd1, sd2, n1, n2)

Arguments

alpha

alpha level for 1-alpha confidence

m1

estamated mean for group 1

m2

estimated mean for group 1

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:

  • Predicted - predicted difference in scores

  • df - degrees of freedom

  • LL - lower limit of the prediction interval

  • UL - upper limit of the prediction interval

References

Hahn GJ (1977). “A prediction interval on the difference between two future sample means and its application to a claim of product superiority.” Technometrics, 19(2), 131–134. ISSN 0040-1706, doi:10.1080/00401706.1977.10489520 .

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

Examples

pi.score2(.05, 19.4, 11.3, 2.70, 2.10, 40, 40)
#>                              Predicted    df       LL       UL
#> Equal Variances Assumed:           8.1 78.00 1.205659 14.99434
#> Equal Variances Not Assumed:       8.1 73.54 1.199067 15.00093

# Should return:
#                              Predicted    df       LL       UL
# Equal Variances Assumed:           8.1 78.00 1.205659 14.99434
# Equal Variances Not Assumed:       8.1 73.54 1.199073 15.00093