categorical.distinguishable.dyad: Estimating nonindependence in distinguishable standard dyadic...

In DLEIVA/DyaDA: Dyadic Data Analysis

Description

A function for estimating dyadic interdependence in standard dyadic designs with distinguishable dyad members and categorical responses.

Usage

   categorical.distinguishable.dyad(dataset, conf.int=0.95)

Arguments

dataset	Original data with dyadic responses.
conf.int	Confidence level in order to estimate the confidence interval for the kappa parameter. It is equal to 0.95 by default.

Details

categorical.distinguishable.dyad estimates dyadic interdependence for any standard dyadic design in which distinguishable members and categorical data are taken into account.

Value

categorical.distinguishable.dyad returns a list containing the following components:

contingency.table	Crosstable for the categorical dyadic data.
kappa	Cohen's kappa statistic for the original data.
alpha	Probability of the parameter not included in the interval estimation.
confidence.interval	Lower and upper bounds of the kappa parameter estimated at 1-alpha confidence level.
z.value	Statistic value for carrying out the statistical test regarding dyadic nonindependence.
standard.error	Standard error for kappa parameter under the null hypothesis of no concordance between dyad members.
two.tailed.p.value	Statistical significance of the z value under the null hypothesis of no concordance between dyad members

Author(s)

David Leiva <[e-mail]>, Antonio Solanas <[e-mail]>, & David A. Kenny <[e-mail]>.

References

Kenny, D. A., Kashy, D. A., & Cook, W. L. (2006). Dyadic data analysis. New York: Guilford Press.

See Also

categorical.indistinguishable.dyad

DLEIVA/DyaDA documentation built on May 6, 2019, 1:17 p.m.