\(\color{blue}{\text{Welcome}}\)

This web page describes faculty activity by Gordon Brooks within the Educational Research and Evaluation (EDRE) program, which is in the Department of Educational Studies and the Patton College of Education at Ohio University.

If you have difficulty accessing these materials for any reason,
please feel free to email me.

\(\color{green}{\text{Information}}\)

\(\color{green}{\text{Recent Publications}}\)

2024

2023

  • Brooks, G. P., SIKA-POKOO, J., ADJANIN, N., & Johanson, G. A. (2023). Cross-loadings in scale development: Monte Carlo study of structural item-total correlation analysis with small samples. General Linear Model Journal, 47(2), 1-15. https://www.glmj.org/archives/GLMJ_2023v47n2.html

  • ADJANIN, N., & Brooks, G. P. (2023). Witnessing the last tropical glaciers: Student use of virtual reality technology to learn about climate change and protecting endangered environments. TOJET: Turkish Online Journal of Educational Technology, 22(4), 248-257. https://www.tojet.net/results.asp?volume=22&issue=4&year=2023

  • ZHOU, Y., REN, X., & Brooks, G. (2023). Which effect size calculation is the best to estimate the population effect size in the Welch t test? Journal of Modern Applied Statistical Methods, 22(1). https://jmasm.com/index.php/jmasm/issue/view/43

  • Brooks, G. P., AN, Q., LI, Y., & Johanson, G. A. (2023). For post hoc’s sake: Determining sample size for Tukey multiple comparisons in 4-Group ANOVA. General Linear Model Journal, 47(1), 1-14. https://www.glmj.org/archives/GLMJ_2023v47n1.html

2022

  • ASEMPAPA, R. S., & Brooks, G. P. (2022). Factor analysis and psychometric evaluation of the mathematical modeling attitude scale for teachers of mathematics. Journal of Mathematics Teacher Education, 25, 131-161. https://doi.org/10.1007/s10857-020-09482-0

  • RUENGVIRAYUDH, P., & Brooks, G. P. (2022). Sample size for parallel analysis and not-so-common criteria for dimensions in factor analysis: Modifying the eigenvalue > 1 Kaiser rule. General Linear Model Journal, 46(1), 20-34. https://www.glmj.org/archives/GLMJ_2022v46n1.html

2021

  • DIAZ, E. A., Brooks, G. P., & Johanson, G. A. (2021). Detecting differential item functioning: Item response theory methods versus the Mantel-Haenszel procedure. International Journal of Assessment Tools in Education, 8(2), 376-393. https://dergipark.org.tr/en/download/article-file/1080666

Before 2021

Wordcloud for Scholarship

\(\color{green}{\text{Recent Conferences}}\)

MWERA 2024

  • ADJANIN, N., MENSAH, F., OTIENO, D. A., & Brooks, G. (2024, October). Seeing shapes in clouds: Using R for qualitative visualizations (yes, you read that right… R… Qualitative). Workshop presented at the annual meeting of the Mid-Western Educational Research Association, Cincinnati.

ATINER 2024 (Shiny App)

  • Brooks, G. P., & ADJANIN, N. (2024, July). Using Human-Friendly Scheffé Comparisons to Explore Group Differences in One-way ANOVA. Presentation at the Athens Institute for Education and Research 18th Annual International Conference on Statistics: Teaching, Theory & Applications. 1-4 July 2024, Athens, Greece. {see the 2024 Program and Abstract links at https://www.atiner.gr/statistics}

AERA 2024

  • LIU, Y., OPPONG, F. A., ADJANIN, N., & Brooks, G. P. (2024, April). The Homogeneity of Covariances Assumption in MANOVA: Differential Impact of Heterogenous Variances and Covariances. Paper presented (assigned to roundtable paper session with paper provided) at the annual meeting of the American Educational Research Association, Philadelphia.
  • OPPONG, F. A., LIU, Y., ADJANIN, N., Johanson, G. A., & Brooks, G. P. (2024, April). Sample Size Determination for (Planned) Post Hoc Multiple Comparisons in One-Way ANOVA. Paper presented (assigned to roundtable paper session with paper provided) at the annual meeting of the American Educational Research Association, Philadelphia.

AERA 2023

  • Brooks, G. P., & ADJANIN, N. (2023, April). Back to the Future: Human-friendly Scheffé Contrasts, or, the Art of Multiple Comparisons. Paper presented at the annual meeting of the American Educational Research Association, Chicago {We chose in-person conference presentation}.

\(\color{green}{\text{Copyright info for Programs}}\)

Documentation

  • Most of the documents available with the programs (e.g., user guides, instructor guides, lesson plans, student exercises) are in Adobe Acrobat PDF format. If you need the Adobe Reader, you can download it from their web site free.

\(\color{green}{\text{Newer Programs for Download}}\)

FISH: Friendly Introductory Statistics Help

  • FISH is a Windows program written in Delphi Pascal that performs introductory descriptive and correlation analyses (last updated January 2022). It is intended to be used as a supplement to introductory statistics courses. It is designed for use in basic statistics courses where a conceptual understanding of statistics is desired without much calculation by hand. It takes the user step-by-step through the calculation of means, standard deviations, z-scores, and correlations. Although some AUXILIARY MATERIALS may have been created for use with a previous version of the program, they should still be very useful with newer versions of the program; that is, changes to the program usually are not dramatic enough to make earlier manuals obsolete. An article about FISH was published in Teaching Statistics and FISH was most recently presented at the annual meeting of the Joint Statistical Meetings, August 2004, Toronto, Canada.

MC2G: Monte Carlo Analyses for 1 or 2 Groups

  • MC2G is a Windows program written in Delphi Pascal that runs Monte Carlo simulations for several single sample and two-sample tests: Independent t, Dependent t, Single-sample t, Mann-Whitney-Wilcoxon, Wilcoxon Signed Rank, Pearson Correlation, Spearman Rank-Order Correlation (last updated 2018). By providing the total number of rejections at the user-specified level of significance, MC2G performs robustness analyses when means are equal (or correlations are zero) and power analyses when the means are not equal (or correlations are non-zero). The original purpose of the program was to assist in the instruction of power analysis and violations of assumptions for introductory educational statistics courses. However, with a little effort the program can be used to answer actual Monte Carlo research questions. MC2G was most recently presented at the annual meeting of the Mid-Western Educational Research Association, October 2003, Columbus, OH, and a program announcement and example lesson plans for MC2G was published in 2003 in Understanding Statistics.

MC4G: Monte Carlo Analyses for up to 4 Groups

  • MC4G is a Windows program written in Delphi Pascal that runs Monte Carlo simulations for One-Way ANOVA with 2, 3, or 4 levels (last updated 2018). By providing the total number of rejections at the user-specified level of significance, MC4G performs robustness analyses when means are equal and power analyses when the means are not equal. It can also be used to estimate required sample sizes. Its initial purpose was to illustrate a variety of Type I Error problems associated with ANOVA (e.g., violations of assumptions, compared to multiple t tests, probability of at least one Type I Error from multiple orthogonal tests). MC4G was most recently presented at the annual meeting of the American Psychological Society, May 2004, Chicago, IL, and an article about MC4G is in press to be published in 2005 in Teaching of Psychology.

MCMR: Monte Carlo for Multiple Regression

  • MCMR is a Windows program written in Delphi Pascal that performs Monte Carlo analyses for Multiple Linear Regression with up to 6 predictors (last updated 2018). The user must specify means and standard deviations as well as correlations, but can also import a single file for analysis. MCMR was most recently presented at the annual meeting of the American Educational Research Association, March 2008, New York, NY, and an article about MCMR was in Multiple Linear Regression Viewpoints (www.glmj.org/).

  • Brooks, G. P. (2008, March). A Monte Carlo program for multiple linear regression. Paper accepted for presentation at the 2008 meeting of the American Educational Research Association, New York, NY.

  • Brooks, G. P. (2008). A Monte Carlo program for multiple linear regression. Multiple Linear Regression Viewpoints, 34(2), 15-43.

  • Download MCMR.EXE

  • Download MCMR.ZIP

  • Instructor’s Guide from AERA 2008

MUD: Messy Ugly Data Generator

  • MUD is a Windows program written in Delphi Pascal that generates data to mimic survey/questionnaire data (last updated 2018). The user can specify item means and standard deviations as well as inter-item correlations. The user can specify an embedded multiple-item scale with separate inter-item correlations (the total scale score is used in calculating correlations for the questionnaire variables).

TAP: Test Analysis Program

  • TAP is a Windows program written in Delphi Pascal that performs test analyses and item analyses based on classical test theory (last updated December 2018). TAP is a classical test and item analysis program. It provides reports for examinee total scores, item statistics (e.g., item difficulty, item discrimination, point-biserial), options analyses, and other useful information. TAP also provides individual examinee reports of total scores and item responses. Although any AUXILIARY MATERIALS may have been created for use with a previous version of the program, they should still be very useful with newer versions of the program; that is, changes to the program usually are not dramatic enough to make earlier manuals obsolete. TAP was most recently presented at the annual meeting of the American Psychological Society, May 2004, Chicago, IL, and a program announcement for TAP was published in 2003 in Applied Psychological Measurement.

\(\color{green}{\text{Older Programs for Download}}\)

BMA: Basic Matrix Algebra (for Statistics)

  • BMA is a Windows program written in Delphi Pascal that performs matrix manipulations (last updated 2004). It is designed for use in advanced statistics courses where a conceptual understanding of matrix algebra is desired without much calculation by hand. It takes the user step-by-step through several matrix algebra functions, including addition, multiplication, transposition, and inversion. BMA was presented most recently at the annual meeting of the Mid-Western Educational Research Association, October 2003, Columbus, OH:

DGW: Data Generator for Windows