Skip to contents

Confidence interval for a tetrachoric correlation

Source: R/statpsych3.R
ci.tetra.Rd

Computes a confidence interval for an approximation to the tetrachoric correlation. This function requires the frequency counts from a 2 x 2 contingency table for two dichotomous variables. This measure of association assumes both of the dichotomous variables are artificially dichotomous. An approximate standard error is recovered from the confidence interval.

For more details, see Section 3.4 of Bonett (2021, Volume 3)

Usage

ci.tetra(alpha, f00, f01, f10, f11)

Arguments

alpha

alpha level for 1-alpha confidence

f00

number of participants with y = 0 and x = 0

f01

number of participants with y = 0 and x = 1

f10

number of participants with y = 1 and x = 0

f11

number of participants with y = 1 and x = 1

Value

Returns a 1-row matrix. The columns are:

  • Estimate - estimate of tetrachoric approximation

  • SE - recovered standard error

  • 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/.

Bonett DG, Price RM (2005). “Inferential methods for the tetrachoric correlation coefficient.” Journal of Educational and Behavioral Statistics, 30(2), 213–225. ISSN 1076-9986, doi:10.3102/10769986030002213 .

Examples

ci.tetra(.05, 86, 16, 7, 93)
#>  Estimate     SE    LL    UL
#>     0.938 0.0268 0.868 0.973

# Should return:
# Estimate     SE    LL    UL
#    0.938 0.0268 0.868 0.973