Problems of Statistical Practices of Educational Researchers

The authors criticized the three types of statistical tests (ANOVA, MANOVA, and ANCOVA) used in the articles published in several prominent educational journals. The problems that authors found include: 1) validity assumptions were not examined, 2) effect size indices were not reported, 3) power analyses were not performed, 4) appropriate references were not cited to communicate the nature of analyses, 5) which statistical software used were not reported.
I believe the same problems exist in the use of other statistical tests in educational papers. This paper can be used as a guide for publishing quantitative studies.
The paper is available at UT e-journals.

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Tags/Keywords	quantitative research, statistics report, APA publishing guide, assumption test
Citation	Keselman, H. J., etc. (1998). Statistical practices of educational researchers: An analysis of their ANOVA, MANOVA, and ANCOVA analysis. Review of Educational Research, 68, 350-386.
Copyright Status	Material is subject to fair use exception
Resource Type	Papers and Reports
Intended Audience	Researchers
Overview	The authors criticized the three types of statistical tests (ANOVA, MANOVA, and ANCOVA) used in the articles published in several prominent educational journals. The problems that authors found include: 1) validity assumptions were not examined, 2) effect size indices were not reported, 3) power analyses were not performed, 4) appropriate references were not cited to communicate the nature of analyses, 5) which statistical software used were not reported. I believe the same problems exist in the use of other statistical tests in educational papers. This paper can be used as a guide for publishing quantitative studies. The paper is available at UT e-journals.
Authors	H. J. Keselman, Carl J. Huberty, Lisa M. Lix, Stephen Olejnik, Robert A. Cribbie, Barbara Donahue, Rhonda K. Kowalchuk, Laureen L. Lowman, Martha D. Petoskey, Joanne C. Keselman, Joel r. Levin
Topic Area	Research Methods - Quantitative data analysis