waba: Within-And-Between-Analysis

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

Description

Conducts Within-And-Between-Analyses and produces a wide range of WABA statistics

Usage

waba(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. The first value in each row (i.e., the first column of values in the data file) must be the individuals' group number/code, which must be an integer. The function sorts individuals into groups on the basis of these numbers/codes. Variable scores appear in subsequent columns. Multiple Variable Analyses (MVA) are conducted when the number of variables = 3, which is a limit that is determined by Hotelling's t-test for dependent correlations. For MVAs involving more than three variables, simply run the function again using new/different combinations of three variables.

Details

Within and between analysis (WABA) was developed by Dansereau, Alutto, and Yammarino (1984). The procedure can process data from groups (not just dyads) of varying sizes, and there are similarities with the Griffin and Gonzalez approaches for dyad-level data described elsewhere in this package. However, the computations in WABA are different, and there is some unique terminology and statistical output.

WABA involves three steps, as described by Yammarino and Markham (1992). First, scores on each variable are examined to determine whether the variance occurs primarily between groups, within groups, or both between and within groups. Next, relationships between variables are examined to determine whether the associations are primarily a function of between-groups covariance, within-groups covariance, or both within- and between-groups covariances. Finally, the results from these two steps are examined for consistency, and appropriate conclusions are drawn.

Produces multiple WABA 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.

Dansereau, F., Chandrasekaran, G., Dumas, M., Coleman, D., Ehrlich, S., & Bagchi, D. (1986). DETECT: Data enquiry that tests entity and correlational/causal theories.Williamsville, NY: Institute For Theory Testing.

Dansereau, F., & Yammarino, F. J. (2000). Within and between analysis: The varient paradigm as an underlying approach to theory building. In K. J. Klein & S.W. J. Kozlowski (Eds.), Multilevel theory, research, and methods in organizations: Foundations, extensions, and new directions (pp. 425-466). San Francisco: Jossey-Bass.

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

Yammarino, F. J., & Markham, S. (1992). On the application of within and between analysis: Are absence and affect really group based. Journal of Applied Psychology, 77, 168-176.

Examples

waba(data_Detect_Set_A)

waba(data_Bliese)

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

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