wabamra: WABA - Multiple Relationship Analysis

In bpoconnor/WABA: Within-and-Between-Analysis for Groups and Dyads

Description

Conducts WABA - Multiple Relationship Analyses, as described by Dansereau et al. (1984) and Yammarino (1984).

Usage

wabamra(data)

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. This function conducts separate WABA analyses for each value of a specified "Condition" variable. The function then conducts Multiple Relationship Analysis comparisons of the WABA coefficients for the different Condition values. The first value in each row (i.e., the first column of values in the data file) must be the Condition number. Condition numbers must be integers. The lowest Condition number cannot be less than one. It is also best for there to be no missing values between the lowest and highest Condition numbers e.g., if the lowest value is 1 and the highest value is 5, then there should also be Condition values of 2, 3, and 4 somewhere in the data file. Gaps in the integers may cause problems. The second value in each row (i.e., the second column of values in the data file) must be the individual's group number/code. The function sorts individuals into groups on the basis of these numbers/codes. Variable scores appear in subsequent columns.

Details

Multiple relationship analyses (MRAs) can be conducted on the WABA results for two or more conditions. The focus in this case is on the identification of moderators or contingencies in WABA patterns. A condition is an additional group variable across which WABA patterns may or may not be consistent. For example, WABA patterns for a given set of variables may vary depending on sex, age group, school type, or neighborhood type. MRA involves pairwise testing for possible differences between WABA correlations for all possible combinations of values of the condition variable of interest. Dansereau et al. (1984) and Yammarino (1998) provided guidelines for interpreting the results from the many MRA contrasts.

Produces multiple WABA MRA statistics.

Author(s)

Brian P. O'Connor

References

Dansereau, F., Alutto, J., & Yammarino, F. (1984). Theory testing in organizational behavior. Englewood Cliffs, NJ: Prentice-Hall.

Yammarino, F. J. (1998). Multivariate aspects of the varient /WABA approach. Leadership Quarterly, 9, 203-227.

Examples

wabamra(data_Detect_Set_A_mra)

wabamra (data_jsp[c('sex','school','english','maths','ravens' )] )

bpoconnor/WABA documentation built on May 13, 2019, 5:22 p.m.