Calcular e apresentar tamanhos do efeito em trabalhos científicos (3): Guia para reportar os tamanhos do efeito para análises de regressão e ANOVAs

• Autores: Helena Maria Amaral Espirito Santo, Fernanda Daniel
• Localización: Revista Portuguesa de Investigação Comportamental e Social: RPICS, ISSN-e 2183-4938, Vol. 4, Nº. 1, 2018 (Ejemplar dedicado a: Fevereiro), págs. 43-60
• Idioma: portugués
• DOI: 10.7342/ismt.rpics.2018.4.1.72
• Títulos paralelos:
  • Calculating and reporting effect sizes on scientific papers (3): Guide to report regression models and ANOVA effect sizes
• Enlaces
  • Texto completo (pdf)
• Dialnet Métricas: 5 Citas
• Resumen
  • English

    In the first issue of the Portuguese Journal of Behavioral and Social Research, the importance of calculating, indicating, and interpreting the effect sizes for the differences of means of two groups (d family of effect sizes) was reviewed. Effect sizes are standard metrics that allows the comparison of the results of statistical analyzes of different studies. Effect sizes also report on the impact of a factor on the variable under investigation and the association between variables.After reviewing the effect sizes for the mean differences between two groups (Espirito-Santo & Daniel, 2015) and most of the r family (Espirito-Santo & Daniel, 2017), the review of effect sizes for analysis of variance was lacking. Analysis of variance can be understood as an extension of the d family to more than two groups (ANOVA) or as an r subfamily in which the proportion of variability is attributable to one or more factors. In the r subfamily reviewed in this study, we analyse the change in the dependent variable that results from one or more independent variables. This analysis is focused on general linear models, including regression models and ANOVA.This article provides the formulas for calculating the most common effect sizes by reviewing the basic concepts of the statistics and providing illustrative examples computed in the Statistical Package for the Social Sciences (SPSS). The guidelines for the interpretation of effect sizes are also presented, as well as the cautions in their use. Also, the article is accompanied by an Excel spreadsheet to facilitate and expedite the calculations for interested readers.

  • português

    No primeiro número da Revista Portuguesa de Investigação Comportamental e Social foi revista a importância de calcular, indicar e interpretar os tamanhos do efeito para as diferenças de médias de dois grupos (família d dos tamanhos do efeito). Os tamanhos do efeito são uma métrica comum que permite comparar os resultados das análises estatísticas de diferentes estudos, informando sobre o impacto de um fator na variável em estudo e sobre a associação entre variáveis.Depois de rever os tamanhos do efeito para as diferenças de médias entre dois grupos (Espirito-Santo e Daniel, 2015) e a maior parte da família r (Espirito-Santo e Daniel, 2017), faltava rever os tamanhos do efeito para a análise da variância. A análise da variância pode ser compreendida como uma extensão da família d a mais de dois grupos (ANOVA) ou como uma subfamília r em que a proporção da variabilidade é imputável a um ou mais fatores. Na subfamília r revista neste estudo, analisa-se a mudança na variável dependente que decorre de uma ou mais variáveis independentes. Esta análise debruça-se sobre os modelos lineares gerais, onde se incluem os modelos de regressão e a ANOVA.Este artigo fornece as fórmulas para calcular os tamanhos do efeito mais comuns, revendo os conceitos básicos sobre as estatísticas e facultando exemplos ilustrativos computados no Statistical Package for the Social Sciences (SPSS). As orientações para a interpretação dos tamanhos do efeito são também apresentadas, assim como as cautelas no seu uso. Adicionalmente, o artigo acompanha-se de uma folha de cálculo em Excel para facilitar e agilizar os cálculos aos interessados.

• Referencias bibliográficas
  • American Psychological Association. (2010). Publication manual of the American Psychological Association (6th ed.). Washington, DC: American...
  • Bakeman, R. (2005). Recommended effect size statistics for repeated measures designs. Behavior Research Methods, 37(3), 379–384.
  • Berben, L., Sereika, S. M., & Engberg, S. (2012). Effect size estimation: methods and examples. International Journal of Nursing Studies,...
  • Bewick, V., Cheek, L., & Ball, J. (2003). Statistics review 7: Correlation and regression. Critical Care, 7(6), 451–459. doi:10.1186/cc2401
  • Bezeau, S., & Graves, R. (2001). Statistical power and effect sizes of clinical neuropsychology research. Journal of Clinical and Experimental...
  • Carroll, R. M., & Nordholm, L. A. (1975). Sampling characteristics of Kelley“s ε2 and Hays” ω2. Educational and Psychological Measurement,...
  • Cohen, J. (1973). Eta-squared and partial eta-squared in fixed factor ANOVA designs. Educational and Psychological Measurement, 33, 107-112....
  • Cohen, J. (1992a). A power primer. Psychological Bulletin, 112(1), 155–159. doi:10.1037/0033-2909.112.1.155
  • Cohen, J. (1992b). Statistical power analysis. Current Directions in Psychological Science, 1(3), 98–101. doi:10.1111/1467-8721.ep10768783
  • Cumming, G. (2012). Understanding the new statistics. New York: Routledge.
  • Ellis, P. D. (2010). The essential guide to effect sizes. Cambridge: Cambridge University Press.
  • Erceg-Hurn, D. M., & Mirosevich, V. M. (2008). Modern robust statistical methods: An easy way to maximize the accuracy and power of your...
  • Espirito-Santo, H., & Daniel, F. B. (2015). Calcular e apresentar tamanhos do efeito em trabalhos científicos (1): As limitações do p...
  • Espirito-Santo, H., & Daniel, F. (2017). Calcular e apresentar tamanhos do efeito em trabalhos científicos (2): Guia para reportar a força...
  • Ferguson, C. J. (2009). An effect size primer: A guide for clinicians and researchers. Professional Psychology: Research and Practice, 40(5),...
  • Field, A. (2005). Effect sizes. Retrieved from http://www.statisticshell.com/docs/effectsizes.pdf
  • Field, A., Miles, J., & Field, Z. (2012). Discovering statistics using R. Londres: Sage.
  • Fisher, R. A. (1925). Statistical methods for research workers. Edinburgh: Oliver & Boyd.
  • Fritz, C. O., Morris, P. E., & Richler, J. J. (2012). Effect size estimates: Current use, calculations, and interpretation. Journal of...
  • Glass, G. V., & Hakstian, A. R. (1969). Measures of association in comparative experiments: Their development and interpretation. American...
  • Haase, R. F., Waechter, D. M., & Solomon, G. S. (1982). How significant is a significant difference? Average effect size of research in...
  • Hair, J., Black, B., Babin, B., & Anderson, R. (2009). Multivariate data analysis (7th ed.). Upper Saddle River: Pearson Higher Ed.
  • Hays, W. L. (1963). Statistics for psychologists. New York: Holt, Rinehart and Winston.
  • Hedges, L. V. (1981). Distribution theory for Glass's estimator of effect size and related estimators. Journal of Educational and Behavioral...
  • Herzberg, P. A. (1969). The parameters of cross-validation. Richmond, VA: William Byrd Press.
  • Ialongo, C. (2016). Understanding the effect size and its measures. Biochemia Medica, 26(2), 150–163. doi:10.11613/BM.2016.015
  • Kelley, K. (2007). Confidence intervals for standardized effect sizes: Theory, application, and implementation. Journal of Statistical Software,...
  • Kelley, T. L. (1935). An unbiased correlation ratio measure. Proceedings of the National Academy of Sciences of the United States of America,...
  • Kennedy, J. J. (1970). The eta coefficient in complex ANOVA designs. Educational and Psychological Measurement, 30(4), 885–889. doi:10.1177/001316447003000409
  • Keppel, G., & Wickens, T. D. (2004). Design and analysis: A researcher's handbook (4th ed.). New Jersey: Pearson
  • Keren, G., & Lewis, C. (1969). Partial omega squared for ANOVA designs. Educational and Psychological Measurement, 39(1), 119–128. doi:10.1177/001316447903900116
  • Keselman, H. J. (1975). A Monte Carlo investigation of three estimates of treatment magnitude: Epsilon squared, eta squared, and omega squared....
  • Keselman, H. J., Algina, J., Lix, L. M., Wilcox, R. R., & Deering, K. N. (2008). A generally robust approach for testing hypotheses and...
  • Kirk, R. E. (1996). Practical significance: A concept whose time has come. Educational and Psychological Measurement, 56(5), 746–759. doi:10.1177/0013164496056005002
  • Kline, R. B. (2013). Beyond significance testing: Reforming data analysis methods in behavioral research (2nd ed.). Washington, DC: American...
  • Lakens, D. (2013). Calculating and reporting effect sizes to facilitate cumulative science: A practical primer for t-tests and ANOVAs. Frontiers...
  • Lenhard, W., & Lenhard, A. (2016). Calculation of effect sizes. doi:10.13140/RG.2.1.3478.4245. Retrieved from https://www.psychometrica.de/effect_size.html.
  • Levine, T. R., & Hullett, C. R. (2002). Eta squared, partial eta squared, and misreporting of effect size in communication research. Human...
  • Lipsey, M. W., Puzio, K., Yun, C., Hebert, M. A., Steinka-Fry, K., Cole, M. W., Roberts, M., Anthony, K. S., & Busick, M. D. (2012). Translating...
  • Lipsey, M. W., & Wilson, D. B. (2001). Practical meta-analysis. New York: Sage Publications, Inc.
  • Lyons, L. C., & Morris, W. A. (2018). The meta analysis calculator. Retrieved from http://www.lyonsmorris.com/ma1/
  • Okada, K. (2013). Is omega squared less biased? Acomparison of three major effect size indices in one-way anova. Behaviormetrika, 40(2), 129–147....
  • Olejnik, S., & Algina, J. (2000). Measures of effect size for comparative studies: Applications, interpretations, and limitations. Contemporary...
  • Olejnik, S., & Algina, J. (2003). Generalized eta and omega squared statistics: Measures of effect size for some common research designs....
  • Pallant, J. (2011). SPSS: Survival manual (4th ed.). Crows Nest: Allen & Unwin.
  • Pampel, F. C. (2000). Logistic regression. Thousand Oaks: SAGE Publications.
  • Pearson, K. (1905). Mathematical contributions to the theory of evolution. XIV. On the general theory of skew correlation and non-linear regression....
  • Pierce, C. A., Block, R. A., & Aguinis, H. (2004). Cautionary note on reporting eta-squared values from multifactor ANOVA designs. Educational...
  • Richardson, J. T. E. (2011). Eta squared and partial eta squared as measures of effect size in educational research. Educational Research...
  • Roberts, J. K., & Henson, R. K. (2002). Correction for bias in estimating effect sizes. Educational and Psychological Measurement, 62(2),...
  • Rosenthal, R. (1991). Meta-analytic procedures for social research (Revised). Newbury Park: Sage.
  • Rosenthal, R. (1994). Science and ethics in conducting, analyzing, and reporting psychological research. Psychological Science, 5(3), 127–134....
  • Rosnow, R. L., & Rosenthal, R. (1989). Statistical procedures and the justification of knowledge in psychological science. The American...
  • Rosnow, R. L., Rosenthal, R., & Rubin, D. B. (2000). Contrasts and correlations in effect-size estimation. Psychological Science, 11(6),...
  • Sechrest, L., & Yeaton, W. H. (2016). Magnitudes of experimental effects in social science research. Evaluation Review, 6(5), 579–600....
  • Smithson, M. (2003). Confidence intervals. Thousand Oaks, CA: Sage.
  • Snyder, P., & Lawson, S. (1993). Evaluating results using corrected and uncorrected effect size estimates. The Journal of Experimental...
  • Steiger, J. H. (2004). Beyond the F test: Effect size confidence intervals and tests of close fit in the analysis of variance and contrast...
  • Steiger, J. H., & Fouladi, R. T. (2016). Noncentrality interval estimation and the evaluation of statistical models. In L. L. Harlow,...
  • Stevens, J. P. (2007). Intermediate statistics (3rd ed.). New York: Lawrence Erlbaum Associates.
  • Steyn, H. S., Jr., & Ellis, S. M. (2009). Estimating an effect size in one-way multivariate analysis of variance (MANOVA). Multivariate...
  • Tabachnick, B. G., & Fidell, L. S. (2007). Using multivariate statistics (5th ed.). Boston: Pearson Education.
  • Thompson, B. (2002). “Statistical,” “practical,” and “clinical”: How many kinds of significance do counselors need to consider? Journal of...
  • Thompson, B. (2007). Effect sizes, confidence intervals, and confidence intervals for effect sizes. Psychology in the Schools, 44(5), 423–432....
  • Vacha-Haase, T., & Thompson, B. (2004). How to estimate and interpret various effect sizes. Journal of Counseling Psychology, 51(4), 473–481....
  • Vaughan, G. M., & Corballis, M. C. (1969). Beyond tests of significance: Estimating strength of effects in selected ANOVA designs. Psychological...
  • Wherry, R. J. (1931). A new formula for predicting the shrinkage of the coefficient of multiple correlation. The Annals of Mathematical Statistics,...
  • Wilkinson, L., & Task Force on Statistical Inference. (1999). Statistical methods in psychology journals: Guidelines and explanations....
  • Wilson, D. B. (2010). Meta-analysis stuff. Retrieved from http://mason.gmu.edu/~dwilsonb/ma.html
  • Wilson, D. B. (2018). Practical meta-analysis effect size calculator. Retrieved from http://cebcp.org/practical-meta-analysis-effect-size-calculator/
  • Zhang, G., & Algina, J. (2011). A robust Root Mean Square Standardized Effect Size in one-way fixed-effects ANOVA. Journal of Modern Applied...