ReadingSkills {bayesbr}R Documentation

Dyslexia and IQ Predicting Reading Accuracy


Data to verify the importance of non-verbal IQ in children's reading skills in dyslexic and non-dyslexic children.




A data frame containing 44 observations on 3 variables.


reading score scaled to the open unit interval (see below).


Is the child dyslexic? If 0, no; If 1, yes.


non-verbal intelligence quotient transformed to z-scores.


The data were collected by Pammer and Kevan (2004). The original precision score was transformed by Smithson and Verkuilen (2006) so that the values of precision are always between 0 to 1, enabling the use of beta regression.

First, the original accuracy was scaled using the minimal and maximal score (a and b, respectively) that can be obtained in the test: (original_accuracy - a) / (b - a) (a and b are not provided). Subsequently, the scaled score is transformed to the unit interval using a continuity correction: (scaled_accuracy * (n-1) - 0.5) / n(either with some rounding or using n = 50 rather than 44).

The dyslexia variable that was a qualitative variable was transformed into a quantitative variable to be used by the package functions.


Example 3 from Smithson and Verkuilen (2006) supplements.


doi: 10.18637/jss.v034.i02 Cribari-Neto, F., and Zeileis, A. (2010). Beta Regression in R. Journal of Statistical Software, 34(2), 1–24.

doi: 10.18637/jss.v048.i11 GrĂ¼n, B., Kosmidis, I., and Zeileis, A. (2012). Extended Beta Regression in R: Shaken, Stirred, Mixed, and Partitioned. Journal of Statistical Software, 48(11), 1–25.

doi: 10.1080/10888430709336633 Pammer, K., and Kevan, A. (2004). The Contribution of Visual Sensitivity, Phonological Processing and Non-Verbal IQ to Children's Reading. Unpublished manuscript, The Australian National University, Canberra.

doi: 10.1037/1082-989X.11.1.54 Smithson, M., and Verkuilen, J. (2006). A Better Lemon Squeezer? Maximum-Likelihood Regression with Beta-Distributed Dependent Variables. Psychological Methods, 11(7), 54–71.


data("ReadingSkills", package = "bayesbr")

bbr = bayesbr(accuracy~iq+dyslexia, iter=1000,warmup=300,

[Package bayesbr version Index]