ggexch: Correlational Analyses of Dyad-Level Data in the...
In bpoconnor/WABA: Within-and-Between-Analysis for Groups and Dyads
Description
Arguments
Details
Author(s)
References
Examples
Description
Conducts correlational analyses of dyad-level data in the
exchangeable-case, based on Griffin & Gonzalez (1995).
Arguments
data
An all-numeric dataframe where the rows are cases & the columns are the variables.
Cases with missing values are not permitted in the data file.
The first collumn of data must contain the dyad numbers (the dyad id# given to both
dyad members). The second and subsequent collumns contain the variables to be analyzed.
Details
The simplest nested data structures are based on dyads. The ggdist function
described elsewhere in this package can be used when the dyadic partners are
distinguishable (and not exchangeable or interchangeable), because they are drawn
from different classes or categories, such as men and women. The ggexch function
can be used for dyad-level data wherein the partners are exchangeable or
interchangeable, as in pairs of men, pairs of women, or pairs of same-sex children.
This function performs the statistical analyses described by Gonzalez and Griffin (1995).
Produces the overall within-partner correlation, the overall cross-partner correlation,
intraclass correlations, and statistics for dyad-level and individual-level effects.
Author(s)
Brian P. O'Connor
References
Griffin, D., & Gonzalez, R. (1995). Correlational analysis of dyadlevel data
in the exchangeable case. Psychological Bulletin, 118, 430-439.
Examples
1
bpoconnor/WABA documentation built on May 13, 2019, 5:22 p.m.
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Description Arguments Details Author(s) References Examples
Description
Conducts correlational analyses of dyad-level data in the exchangeable-case, based on Griffin & Gonzalez (1995).
Arguments
data |
An all-numeric dataframe where the rows are cases & the columns are the variables. Cases with missing values are not permitted in the data file. The first collumn of data must contain the dyad numbers (the dyad id# given to both dyad members). The second and subsequent collumns contain the variables to be analyzed. |
Details
The simplest nested data structures are based on dyads. The ggdist function described elsewhere in this package can be used when the dyadic partners are distinguishable (and not exchangeable or interchangeable), because they are drawn from different classes or categories, such as men and women. The ggexch function can be used for dyad-level data wherein the partners are exchangeable or interchangeable, as in pairs of men, pairs of women, or pairs of same-sex children. This function performs the statistical analyses described by Gonzalez and Griffin (1995).
Produces the overall within-partner correlation, the overall cross-partner correlation, intraclass correlations, and statistics for dyad-level and individual-level effects.
Author(s)
Brian P. O'Connor
References
Griffin, D., & Gonzalez, R. (1995). Correlational analysis of dyadlevel data in the exchangeable case. Psychological Bulletin, 118, 430-439.
Examples
1 |
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