PLEASE USE INTERNET EXPLORER TO RUN THESE PROGRAMS. If you cannot see the applets on this page, please
download the java plug-in here. To automatically download the Java
plug-in click
here. If the programs are blocked due to "security concerns" or "out of date" applets, click on the following link to read instructions on how to add exceptions to be able to run the programs:
RunningJava.pdf
Click here to read a
review of this book published in International Journal of Consumer
Studies (January 2005)
Click here to read a review of this
book published in Organizational Research Methods (January 2005)
This program was used to create the data set for Chapter 3. The program is a multivariate random
normal scores generator that uses the Box and Muller and Choleski Factorization algorithms.
Click here to download the source code and executable versions of
the program.
Source: Aguinis, H. (1994). A QuickBasic program for generating correlated
multivariate random normal scores. Educational and Psychological Measurement, 54, 687-689.
[click here to view article]
Pay for Performance Data Set for Chapter 3
Click here to download the data file described in Chapter 3.
The data file is included in SPSS and excel formats.
ALTMMR
This program is described in Chapter 4. It checks whether the homogeneity
of error variance assumption has been violated and conducts a test for moderation using
analyses other than MMR when there is a violation of the assumption.
Click here to download the source code and executable versions of ALTMMR.
Source: Aguinis, H., Petersen, S. A., & Pierce, C. A. (1999). Appraisal of
the homogeneity of error variance assumption and alternatives to multiple regression for
estimating moderating effects of categorical variables. Organizational Research Methods, 2, 315-339.
[click
here
to view article]
CAQ
This program is described in Chapter 6. It administers questionnaires on IBM and
IBM-compatible personal computers by prompting respondents to indicate their answer by
clicking on a graphic line segment displayed on the screen.
Click here to download the source code and executable versions of CAQ.
Source: Aguinis, H., Bommer, W. H., & Pierce, C. A. (1996).
Improving the estimation of moderating effects by using computer-administered questionnaires.
Educational and Psychological Measurement, 56, 1043-1047. [click
here
to view article]
POWER
This program is described in Chapter 7. It estimates the statistical power to detect a
dichotomous moderator variable using moderated multiple regression (MMR).
It computes power for specified conditions of effect size (i.e., absolute difference between
subgroup correlation coefficients), total sample size, and sample sizes in moderator-based
subgroups.
Click here to download the source code and executable versions of POWER.
Source: Aguinis, H., Pierce, C. A., & Stone-Romero, E. F. (1994).
Estimating the power to detect dichotomous moderators with moderated multiple regression.
Educational and Psychological Measurement, 54, 690-692. [click
here to view article]
MMRPWR
This program is described in Chapter 7. It estimates the statistical power to detect
a dichotomous moderator variable with MMR specified conditions of effect size
(i.e., absolute difference between subgroup correlation coefficients), total sample size,
sample sizes in moderator-based subgroups, predictor-moderator intercorrelation,
and predictor variable range restriction.
Click here to download the source code and executable versions of MMRPWR.
Source: Aguinis, H., & Pierce, C. A. (1998). Statistical power computations for
detecting dichotomous moderator variables with moderated multiple regression. Educational
and Psychological Measurement, 58, 668-676. [click
here to view
article]
MMRPOWER
This program is described in Chapter 7 and Chapter 8. It estimates statistical power using a theory-based
approximation. It can be used for moderators with more than 2 levels.
Source: Aguinis, H., Boik, R.J., & Pierce, C.A. (2001). A generalized solution for approximating the power
to detect effects of categorical moderator variables using multiple regression.
Organizational Research Methods,
4, 291-323. [click
here
to view article]
f 2
This program computes the modified f 2 moderating effect size index described in Chapter 9.
Click here to download the source code and executable
versions of this program.
Source for Algorithm: Aguinis, H., Beaty, J. C., Boik, R. J., & Pierce, C. A.
(2005). Effect size and power in assessing moderating effects of categorical
variables using multiple regression: A 30-year review. Journal of Applied
Psychology, 90, 94-107. [click
here to view article]
Source for
Program: Aguinis, H., & Pierce, C. A.
(2006). Computation of effect size for moderating effects of categorical
variables in multiple regression. Applied
Psychological Measurement, 30, 440-442. [click
here to
view article]
