Reading: Reading Skills data
In FlexReg: Regression Models for Bounded Continuous and Discrete Responses
Reading R Documentation
Reading Skills data
Description
Data for assessing the contribution of non-verbal IQ to children's reading skills in dyslexic and non-dyslexic children.
Format
A data.frame containing 44 observations on 4 variables.
accuracya reading score.
accuracy.adjthe adjusted reading score: the observed 1's (perfect reading scores) are substituted with 0.99.
dyslexiaa factor indicating wheter the child is dyslexic.
iqa standardized quantitative measure of the children's non verbal abilities.
Details
The data were originally analyzed by Pammer and Kevan (2004) and successively used by Smithson and Verkuilen (2006) and by Migliorati et al. (2018).
Source
References
Cribari-Neto, F., Zeileis, A. (2010). Beta Regression in R. Journal of Statistical Software, 34(2), 1–24.
Di Brisco, A. M., Migliorati, S. (2020). A new mixed-effects mixture model for constrained longitudinal data. Statistics in Medicine, 39(2), 129–145. doi:10.1002/sim.8406
Migliorati, S., Di Brisco, A. M., Ongaro, A. (2018). A New Regression Model for Bounded Responses. Bayesian Analysis, 13(3), 845–872. doi:10.1214/17-BA1079
Smithson, M., Verkuilen, J. (2006). A Better Lemon Squeezer? Maximum-Likelihood Regression with Beta-Distributed Dependent Variables. Psychological Methods, 11(7), 54–71.
FlexReg documentation built on Sept. 29, 2023, 9:06 a.m.
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| Reading | R Documentation |
Reading Skills data
Description
Data for assessing the contribution of non-verbal IQ to children's reading skills in dyslexic and non-dyslexic children.
Format
A data.frame containing 44 observations on 4 variables.
accuracya reading score.
accuracy.adjthe adjusted reading score: the observed 1's (perfect reading scores) are substituted with 0.99.
dyslexiaa factor indicating wheter the child is dyslexic.
iqa standardized quantitative measure of the children's non verbal abilities.
Details
The data were originally analyzed by Pammer and Kevan (2004) and successively used by Smithson and Verkuilen (2006) and by Migliorati et al. (2018).
Source
References
Cribari-Neto, F., Zeileis, A. (2010). Beta Regression in R. Journal of Statistical Software, 34(2), 1–24.
Di Brisco, A. M., Migliorati, S. (2020). A new mixed-effects mixture model for constrained longitudinal data. Statistics in Medicine, 39(2), 129–145. doi:10.1002/sim.8406
Migliorati, S., Di Brisco, A. M., Ongaro, A. (2018). A New Regression Model for Bounded Responses. Bayesian Analysis, 13(3), 845–872. doi:10.1214/17-BA1079
Smithson, M., Verkuilen, J. (2006). A Better Lemon Squeezer? Maximum-Likelihood Regression with Beta-Distributed Dependent Variables. Psychological Methods, 11(7), 54–71.
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
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