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LEUKOS
The Journal of the Illuminating Engineering Society
Volume 15, 2019 - Issue 2-3: Lighting Research Methods
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Review Articles

Power Analysis, Sample Size, and Assessment of Statistical Assumptions—Improving the Evidential Value of Lighting Research

Pages 143-162 | Received 01 Mar 2018, Accepted 05 Oct 2018, Published online: 25 Jan 2019

References

  • Abelson RP. 1995. Statistics as principled argument. Hillsdale (NJ): Lawrence Erlbaum Associates.
  • Albers C, Lakens D. 2018. When power analyses based on pilot data are biased: inaccurate effect size estimators and follow-up bias. Journal of Experimental Social Psychology. 74:187–95.
  • Appelbaum M, Cooper H, Kline RB, Mayo-Wilson E, Nezu AM, Rao SM. 2018. Journal article reporting standards for quantitative research in psychology: the APA publications and communications board task force report. American Psychologist. 73(1):3–25.
  • Bakker M, Hartgerink CH, Wicherts JM, van der Maas HL. 2016. Researchers’ intuitions about power in psychological research. Psychological Science. 27(8):1069–77.
  • Bakker M, Wicherts JM. 2011. The (mis) reporting of statistical results in psychology journals. Behavior Research Methods. 43(3):666–78.
  • Benjamin DJ, Berger JO, Johannesson M, Nosek BA, Wagenmakers EJ, Berk R, … Cesarini D. 2017. Redefine statistical significance. Nature Human Behaviour. 2:6-10.
  • Berry WD (1993). Understanding regression assumptions. Sage university paper series on quantitative applications in the social sciences, 07-092. Newbury Park (CA): Sage.
  • Boyce PR, Cuttle C. 1990. Effect of correlated colour temperature on the perception of interiors and colour discrimination performance. Lighting Research & Technology. 22(1):19–36.
  • Button KS, Ioannidis JP, Mokrysz C, Nosek BA, Flint J, Robinson ES, Munafò MR. 2013. Power failure: why small sample size undermines the reliability of neuroscience. Nature Reviews Neuroscience. 14(5):365–76.
  • Cengiz C, Puolakka M, Halonen L. 2015. Reaction time measurements under mesopic light levels: towards estimation of the visual adaptation field. Lighting Research & Technology. 47(7):828–44.
  • Cohen BH. 2013. Explaining psychological statistics. 4th ed. New York (NY): Wiley.
  • Cohen J. 1988. Statistical power analysis for the beahavioral sciences. New York (NY): Lawrence Erlbaum Associates.
  • Cohen J. 1992. A power primer. Psychological Bulletin. 112(1):155–59.
  • Conover WJ. 1999. Nonparametric statistics. 3rd ed. New York (NY): John Wiley and Sons.
  • Davis RG, Ginthner DN. 1990. Correlated color temperature, illuminance level, and the Kruithof curve. Journal of the Illuminating Engineering Society. 19(1):27–38.
  • Dawson R. 2011. How significant is a boxplot outlier? Journal of Statistics Education. 19(2). [Accessed 14 February 2018]. http://ww2.amstat.org/publications/jse/v19n2/dawson.pdf.
  • Delacre M, Lakens D, Leys C. 2017. Why psychologists should by default use Welch’s t-test instead of student’s t-test. International Review of Social Psychology. 30(1):92–101.
  • DiLaura DL, Houser KW, Mistrick RG, Steffy GR. 2011. The lighting handbook. 10th ed. New York (NY): IESNA.
  • Dorey F. 2010. In brief: the P value: what is it and what does it tell you? Clinical Orthopaedics and Related Research. 468(8):2297–98.
  • Dumas-Mallet E, Button KS, Boraud T, Gonon F, Munafò MR. 2017. Low statistical power in biomedical science: a review of three human research domains. Royal Society Open Science. 4(2):160254.
  • Dunlap WP, Cortina JM, Vaslow JB, Burke MJ. 1996. Meta-analysis of experiments with matched groups or repeated measures designs. Psychological Methods. 1(2):170–77.
  • Durlak JA. 2009. How to select, calculate, and interpret effect sizes. Journal of Pediatric Psychology. 34(9):917–28.
  • Erceg-Hurn DM, Mirosevich VM. 2008. Modern robust statistical methods: an easy way to maximize the accuracy and power of your research. American Psychologist. 63(7):591–601.
  • Erdfelder E, Faul F, Buchner A. 1996. GPOWER: A general power analysis program. Behavior Research Methods, Instruments, & Computers. 28:1–11.
  • Fanelli D. 2010. “Positive” results increase down the hierarchy of the sciences. PloS one. 5(4):e10068.
  • Field A, Miles J, Field Z. 2012. Discovering statistics using R. London (UK): Sage Publications.
  • Fisher RA. 1925. Statistical methods for research workers. Edinburgh (UK): Oliver & Boyd.
  • Flynn JE, Hendrick C, Spencer T, Martyniuk O. 1979. A guide to methodology procedures for measuring subjective impressions in lighting. Journal of the Illuminating Engineering Society. 8(2):95–110.
  • Fotios S. 2017. A revised Kruithof graph based on empirical data. Leukos. 13(1):3–17.
  • Fotios S, Atli D, Cheal C, Houser K, Logadóttir Á. 2015. Lamp spectrum and spatial brightness at photopic levels: A basis for developing a metric. Lighting Research & Technology. 47(1):80–102.
  • Fotios S, Cheal C, Fox S, Uttley J. 2017. The effect of fog on detection of driving hazards after dark. Lighting Research & Technology. Advance online publication. doi:10.1177/1477153517725774.
  • Fotios S, Goodman T. 2012. Proposed UK guidance for lighting in residential roads. Lighting Research & Technology. 44(1):69–83.
  • García-Berthou E, Alcaraz C. 2004. Incongruence between test statistics and P values in medical papers. BMC Medical Research Methodology. 4(1):13.
  • Ghasemi A, Zahediasl S. 2012. Normality tests for statistical analysis: a guide for non-statisticians. International Journal of Endocrinology and Metabolism. 10(2):486–89.
  • Grosjean P, Ibanez F 2014. Pastecs: package for analysis of space-time ecological series. R package version 1.3-18. https://CRAN.R-project.org/package=pastecs.
  • Haslam A, McGarty C. 2018. Research methods and statistics in psychology. 3rd ed. London (UK): Sage.
  • He Y, Rea M, Bierman A, Bullough J. 1997. Evaluating light source efficacy under mesopic conditions using reaction times. Journal of the Illuminating Engineering Society. 26(1):125–38.
  • Hoenig JM, Heisey DM. 2001. The abuse of power: the pervasive fallacy of power calculations for data analysis. The American Statistician. 55(1):19–24.
  • Hubbard R, Ryan PA. 2000. The historical growth of statistical significance testing in psychology—and its future prospects. Educational and Psychological Measurement. 60(5):661–81.
  • Ioannidis JP. 2005. Why most published research findings are false. PLoS Medicine. 2(8):e124.
  • Jefferson T, Alderson P, Wager E, Davidoff F. 2002. Effects of editorial peer review: a systematic review. Jama. 287(21):2784–86.
  • Joanes DN, Gill CA. 1998. Comparing measures of sample skewness and kurtosis. Journal of the Royal Statistical Society: Series D (The Statistician). 47(1):183–89.
  • John LK, Loewenstein G, Prelec D. 2012. Measuring the prevalence of questionable research practices with incentives for truth telling. Psychological Science. 23(5):524–32.
  • Kashy DA, Donnellan MB, Ackerman RA, Russell DW. 2009. Reporting and interpreting research in PSPB: practices, principles, and pragmatics. Personality and Social Psychology Bulletin. 35(9):1131–42.
  • Kruithof AA. 1941. Tubular luminescence lamps for general illumination. Phillips Technical Review. 6:65–73.
  • Lakens D. 2013. Calculating and reporting effect sizes to facilitate cumulative science: a practical primer for t-tests and ANOVAs. Frontiers in Psychology. 4:863.
  • Lakens D, Adolfi FG, Albers CJ, Anvari F, Apps MA, Argamon SE, … Buchanan EM. 2018. Justify your alpha. Nature Human Behaviour. 2(3):168–71.
  • Lemoine NP, Hoffman A, Felton AJ, Baur L, Chaves F, Gray J, … Smith MD. 2016. Underappreciated problems of low replication in ecological field studies. Ecology. 97(10):2554–61.
  • Massidda D 2013. retimes: reaction time analysis. R package version 0.1.2. https://CRAN.R-project.org/package=retimes.
  • McDonald JH. 2014. Handbook of biological statistics. 3rd ed. Baltimore (Maryland): Sparky House Publishing.
  • McShane BB, Gal D, Gelman A, Robert C, Tackett JL 2017. Abandon statistical significance. arXiv preprint arXiv:1709.07588.
  • Motulsky H. 1995. Intuitive biostatistics. New York (NY): Oxford University Press.
  • Nuijten MB, Hartgerink CH, van Assen MA, Epskamp S, Wicherts JM. 2016. The prevalence of statistical reporting errors in psychology (1985–2013). Behavior Research Methods. 48(4):1205–26.
  • Olivier J, May WL, Bell ML. 2017. Relative effect sizes for measures of risk. Communications in Statistics-Theory and Methods. 46(14):6774–81.
  • Open Science Collaboration. 2015. Estimating the reproducibility of psychological science. Science. 3496251:aac4716.
  • Palmer EM, Horowitz TS, Torralba A, Wolfe JM. 2011. What are the shapes of response time distributions in visual search? Journal of Experimental Psychology: Human Perception and Performance. 37(1):58.
  • Paterson TA, Harms PD, Steel P, Credé M. 2016. An assessment of the magnitude of effect sizes: evidence from 30 years of meta-analysis in management. Journal of Leadership & Organizational Studies. 23(1):66–81.
  • Pearson ES, Hartley HO. 1976. Biometrika tables for statisticians. Vol. I. 3rd ed. New York (NY): Cambridge University Press.
  • Quintana DS. 2017. Statistical considerations for reporting and planning heart rate variability case‐control studies. Psychophysiology. 54(3):344–49.
  • R Core Team. 2017. R: A language and environment for statistical computing. Vienna (Austria): R Foundation for Statistical Computing. https://www.R-project.org/
  • Razali NM, Wah YB. 2011. Power comparisons of shapiro-wilk, kolmogorov-smirnov, lilliefors and anderson-darling tests. Journal of Statistical Modeling and Analytics. 2(1):21–33.
  • Rea MS, Illuminating Engineering Society of North America. 1993. IESNA lighting handbook. 8th ed. New York (NY): IESNA.
  • Rosnow RL, Rosenthal RR. 2003. Effect sizes for experimenting psychologists. Canadian Journal of Experimental Psychology. 57(3):221–37.
  • Rothman KJ. 2014. Six persistent research misconceptions. Journal of General Internal Medicine. 29(7):1060–64.
  • Ruxton GD, Neuhäuser M. 2010. When should we use one‐tailed hypothesis testing? Methods in Ecology and Evolution. 1(2):114–17.
  • Schmider E, Ziegler M, Danay E, Beyer L, Bühner M. 2010. Is it really robust? Reinvestigating the robustness of ANOVA against violations of the normal distribution assumption. Methodology. 6:147–51.
  • Shapiro SS, Wilk MB. 1965. An analysis of variance test for normality (complete samples). Biometrika. 52:591–611.
  • Siegel SC, Castellan NJ. 1988. Nonparametric statistics for the behavioural sciences. New York (NY): McGraw-Hill.
  • Simmons JP, Nelson LD, Simonsohn U. 2011. False-positive psychology: undisclosed flexibility in data collection and analysis allows presenting anything as significant. Psychological Science. 22(11):1359–66.
  • Simons RH, Hargroves RA, Pollard NE, Simpson MD. 1987. Lighting criteria for residential roads and areas. Venice (Italy): CIE; p. 274–77.
  • Sterling TD, Rosenbaum WL, Weinkam JJ. 1995. Publication decisions revisited: the effect of the outcome of statistical tests on the decision to publish and vice versa. The American Statistician. 49(1):108–12.
  • Sullivan GM, Feinn R. 2012. Using effect size—or why the P value is not enough. Journal of Graduate Medical Education. 4(3):279–82.
  • Thiese MS, Arnold ZC, Walker SD. 2015. The misuse and abuse of statistics in biomedical research. Biochemia Medica. 25(1):5–11.
  • Tversky A, Kahneman D. 1971. Belief in the law of small numbers. Psychological Bulletin. 76(2):105–10.
  • Veitch JA. 2001. Psychological processes influencing lighting quality. Journal of the Illuminating Engineering Society. 30(1):124–40.
  • Ware M. 2008. Peer review: benefits, perceptions and alternatives. PRC Summary Papers. 4:4–20.
  • Wilcox RR. 1998. How many discoveries have been lost by ignoring modern statistical methods? American Psychologist. 53(3):300–14.
  • Wilkinson L. 1999. Statistical methods in psychology journals: guidelines and explanations. American Psychologist. 54(8):594–604.
  • Williams MN, Gómez Grajales CA, Kurkiewicz D. 2013. Assumptions of multiple regression: correcting two misconceptions. Practical Assessment, Research & Evaluation. 18(11):1–14.
  • Yap BW, Sim CH. 2011. Comparisons of various types of normality tests. Journal of Statistical Computation and Simulation. 81(12):2141–55.