Confidence interval for an exponentiated slope

Computes confidence intervals for exp(B) - 1 (as a percent) and exp(B) where B is a population slope coefficient in a binary logit, ordinal logit, or log-Poisson model. This function is useful with software that does not have an option to compute exp(B) and exp(B) - 1.

For more details, see Section 4.1 of Bonett (2021, Volume 3)

Usage

expon.slope(alpha, b, se)

Arguments

alpha: alpha level for 1-alpha confidence
b: estimated slope coefficient
se: slope standard error

Value

Returns a 2-row matrix. The first row gives the results for exp(B), and the the second row gives the results for exp(B) - 1 (as a percent). The columns are:

Estimate - estimate of exp(B) or exp(B) - 1
LL - lower limit of the confidence interval
UL - upper limit of the confidence interval

References

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

Examples

expon.slope(.05, .502, .0396)
#>                   Estimate        LL       UL
#> exp(B)            1.652022  1.528651  1.78535
#> 100[exp(B) - 1]% 65.202201 52.865066 78.53502

# Should return:
#                   Estimate        LL       UL
# exp(B)            1.652022  1.528651  1.78535
# 100[exp(B) - 1]% 65.202201 52.865066 78.53502