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source: https://stackoverflow.com/questions/58980300/error-converting-between-discrete-and-numeric-variables-with-ggstatsplot
# setup set.seed(123) library(ggstatsplot) #> Registered S3 method overwritten by 'broom.mixed': #> method from #> tidy.gamlss broom #> Registered S3 methods overwritten by 'car': #> method from #> influence.merMod lme4 #> cooks.distance.influence.merMod lme4 #> dfbeta.influence.merMod lme4 #> dfbetas.influence.merMod lme4 # data df <- structure(list(condition = structure(c( 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L ), .Label = c( "0", "1", "2", "3" ), class = "factor"), size = c( 3, 1, 1, 2, 5, 4, 5, 3, 1, 1, 4, 3, 5, 4, 4, 4, 2, 2, 4, 5, 3, 3, 3, 3, 5, 1, 5, 5, 5, 1, 3, 4, 2, 1, 2, 1, 1, 3, 3, 1, 2, 3, 1, 4, 5, 5, 1, 5, 4, 5, 5, 1, 1, 4, 1, 2, 5, 1, 2, 2, 5, 3, 3, 4, 5, 3, 3, 3, 2, 1, 2, 4, 1, 1, 4, 4, 1, 2, NA, 3, 1, 4, 4, 2, 3, 4, 4, 4, 3, 5, 4, 2, 2, 5, 5, 5, 4, 1, 2, 5, 5 ), predict = c( 4, 4, 1, 1, 1, 4, 2, 4, 3, 2, 2, 3, 1, 1, 4, 3, 5, 2, 4, 2, 1, 5, 3, 3, 3, 3, 4, 2, 1, 1, 5, 2, 5, 3, 3, 3, 1, 5, 2, 3, 5, 2, 2, 5, 3, 2, 1, 4, 2, 2, 4, 4, 1, 4, 3, 3, 1, 1, 2, 3, 4, 4, 2, 5, 4, 3, 2, 3, 4, 4, 5, 2, 2, 4, 2, 2, 5, 4, NA, 1, 2, 3, 3, 5, 5, 5, 5, 1, 1, 1, 2, 1, 4, 2, 1, 2, 5, 3, 1, 4, 5 ), meaningful = c( 6, 5, 3, 3, 5, 4, 3, 2, 4, 6, 6, 4, 2, 2, 4, 5, 2, 5, 2, 4, 5, 1, 2, 7, 5, 7, 6, 3, 4, 4, 3, 7, 2, 2, 2, 4, 3, 3, 1, 6, 7, 1, 5, 1, 7, 4, 1, 2, 3, 4, 1, 1, 4, 1, 7, 3, 4, 7, 6, 6, 2, 5, 5, 6, 4, 3, 5, 6, 4, 1, 1, 2, 1, 4, 7, 5, 4, 6, NA, 5, 5, 6, 7, 4, 3, 7, 7, 5, 4, 3, 1, 5, 5, 1, 6, 1, 5, 2, 5, 2, 1 )), row.names = c( NA, -101L ), class = c("tbl_df", "tbl", "data.frame")) # plot ggbetweenstats( data = df, x = condition, y = meaningful ) #> Note: 95% CI for effect size estimate was computed with 100 bootstrap samples. #> #> Note: Shapiro-Wilk Normality Test for meaningful: p-value = < 0.001 #> #> Note: Bartlett's test for homogeneity of variances for factor condition: p-value = 0.284 #> #> Error: Discrete value supplied to continuous scale
Created on 2019-11-22 by the reprex package (v0.3.0)
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source: https://stackoverflow.com/questions/58980300/error-converting-between-discrete-and-numeric-variables-with-ggstatsplot
Created on 2019-11-22 by the reprex package (v0.3.0)
Session info
The text was updated successfully, but these errors were encountered: