A robust function to return the cumulative density of non-central F distributions in Microsoft Office Excel

  1. James Byron Nelson 1
  1. 1 University of the Basque Country (UPV/EHU)
Aldizkaria:
Psicológica: Revista de metodología y psicología experimental

ISSN: 1576-8597

Argitalpen urtea: 2016

Alea: 37

Zenbakia: 1

Orrialdeak: 61-83

Mota: Artikulua

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Beste argitalpen batzuk: Psicológica: Revista de metodología y psicología experimental

Laburpena

The manuscript presents a Visual Basic® for Applications function that operates within Microsoft Office Excel® to return the area below the curve for a given F within a specified non-central F distribution. The function will be of use to Excel users without programming experience wherever a noncentral F distribution is required, such as conducting power analyses for analysis of variance designs and constructing confidence intervals on effect sizes. Tests show the function to produce results comparable to those obtained with the commercial software SPSS and the popular free R environment for statistical computing. Spreadsheets for use in Excel and OpenOffice Calc® are included with example usages.

Erreferentzia bibliografikoak

  • Cummings, G., & Finch, S. (2001). A primer on the understanding, use and calculation of confidence intervals that are based on central and noncentral distributions. Educational and Psychological Measurement, 61, 633-649.
  • Faul, F., Erdfelder, E., Lang, A.-G., & Buchner, A. (2007). G*Power 3: A flexible statistical power analysis program for the social, behavioral, and biomedical sciences. Behavior Research Methods, 39, 175-191.
  • Fidler, F., & Thompson, B. (2001) Computing correct confidence intervals for ANOVA fixed- and random-effects effect sizes. Educational and Psychological Measurement, 61, 575-604.
  • Finch, W.H., & French, B.F. (2012). A comparison of methods for estimating confidence intervals for Omega-Squared effect size. Educational and Psychological Measurement, 72, 68-77.
  • Fritz, C. O., Morris, P. E., & Richler, J.L. (2012). Effect size estimates: Current use, calculations and interpretation. Journal of Experimental Psychology: General, 141, 2-18.
  • Howell, D.C. (1987) Statistical Methods for Psychology, 2nd Edition. Boston: PWS-Kent
  • IBM Corp. (2011). IBM SPSS Statistics for Windows, Version 20.0. Armonk, NY: IBM Corp
  • R Core Team (2014). R: A language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria. URL http://www.R-project.org/
  • SAS Institute Inc (2014). SAS, Version 9.4. Cary, NC.
  • Smithson, M. (2001). Correct confidence intervals for various regression effect sizes and parameters: The importance of noncentral distributions in computing intervals. Educational and Psychological Measurement, 61, 603-630.
  • Teixeira, A., & Rosa, A., & Calapez A. (2009). Statistical power analysis with Microsoft Excel: Normal tests for one or two means as a prelude to using non-central distributions to calculate power. Journal of Statistics Education, 17, 1-21
  • JARS Groiup: The American Psychological Association Working Group on Journal Article Reporting Standards. (2008). Reporting Standards for Research in Psychology: Why Do We Need Them? What Might They Be? American Psychologist, 63(9), 839-851
  • The Math Works Inc (2014). MATLAB- The language of technical computing, Version R2014B, Natick, Massachusetts.
  • Wilkinson, L., & the Task Force on Statistical Inference. (1999). Statistical methods in psychology journals: Guidelines and explanations. American Psychologist, 54, 594-604.
  • Zaiontz C. (2015) Real Statistics Using Excel. www.real-statistics.com
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