Error Bars In Repeated Measures
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error bars let the audience know the amount of uncertainty in the data, and see how much of the variance is explained by the reported effect of an experiment. representing error bars in within-subject designs in typical software packages While this is straightforward for between-subject variables, it's less clear for mixed- and morey 2008 repeated-measures designs. Consider the following. When running an ANOVA, the test accounts for three sources of variance: 1) the loftus and masson 1994 fixed effect of the condition, 2) the ability of the participants, and 3) the random error, as data = model + error. Plotting the repeated-measures without taking the different sources of using confidence intervals in within-subject designs. variance into consideration would result in overlapping error bars that include between-subject variability, confusing the presentation's audience. While the ANOVA partials out the differences between the participants and allow you to assess the effect of the repeated-measure, computing a regular confidence interval by multiplying the standard error and the F-statistic doesn't work in this way. Winston Chang has developed a set of
Cousineau (2005)
R functions based on Morey (2008) and Cousineau (2005) on his wiki that help deal with this problem, where the sample variance is computed for the normalized data, and then multiplied by the sample variances in each condition by M(M-1), where M is the number of within-subject conditions. See his wiki here for more info. References Morey, R. D. (2008). Confidence Intervals from Normalized Data: A correction to Cousineau (2005). Cousineau,D. (2005). Confidence intervals in within‐subject designs:A simpler solution to Loftus and Masson’s method. Loftus, G.R., & Masson, M.E.J. (1994). Using confidence intervals in within‐subject designs. Posted by Jason A. French Mar 7th, 2012 R, ggplot2, repeated-measures Tweet « Using Figures within Tables in LaTeX Analyzing Qualtrics Data in R using Github Packages » Comments Please enable JavaScript to view the comments powered by Disqus. Recent Posts Summer Reading on Data Science Recursion in R Installing old R packages for new installations Using R with MySQL Databases Fixing knitr: Formatting statistical output to 2 digits in R GitHub Repos Status updating... @frenchja on GitHub Google+ Popular Posts Using Figures within Tables in LaTeX Graphing Error Bars
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Within Subject Error
Us Learn more about Stack Overflow the company Business Learn more about hiring developers standard error bars for repeated measures or posting ads with us Cross Validated Questions Tags Users Badges Unanswered Ask Question _ Cross Validated is a question calculating and graphing within-subject confidence intervals for anova and answer site for people interested in statistics, machine learning, data analysis, data mining, and data visualization. Join them; it only takes a minute: Sign up Here's how it works: Anybody can ask http://frenchja.github.com/blog/2012/03/07/graphing-error-bars-for-repeated-measures-variables-with-ggplot2/ a question Anybody can answer The best answers are voted up and rise to the top Is using error bars for means in a within-subjects study wrong? up vote 5 down vote favorite 1 I seem to recall one of my professors saying that error bars are completely uninformative when comparing repeated measures taken from a single group. Is that true? Surely many studies compute the sample means http://stats.stackexchange.com/questions/133014/is-using-error-bars-for-means-in-a-within-subjects-study-wrong for condition A and for condition B (i.e. levels A and B of a certain within-subjects factor), compare the means with a paired samples t-test, and then display them on a graph with error bars. Is this really wrong? If so, why? confidence-interval data-visualization repeated-measures t-test share|improve this question edited Jan 11 '15 at 17:50 gung 73.9k19160309 asked Jan 11 '15 at 17:00 wildetudor 3901314 1 Not quite a direct answer to your question, but there are a few different methods that are supposed to calculate meaningful error bars for within-subjects data, e.g. this method proposed by Cousineau and O'Brien. (apologies if this is not accessible, I'm on a university computer and can't tell if it's an open access article or just using my institutional access automatically) –Marius Jan 12 '15 at 5:41 Thanks, this is helpful to know! –wildetudor Jan 12 '15 at 9:22 add a comment| 1 Answer 1 active oldest votes up vote 9 down vote accepted It isn't "wrong" necessarily, and it isn't "completely uninformative". But it provides information that pertains to a largely unrelated question, and so is likely to be misleading. When you run a paired samples $t$-test, you are re
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