Reading

Data for assessing the contribution of non-verbal IQ to children's reading skills in dyslexic and non-dyslexic children.

Functions to fit regression models for bounded responses (e.g., proportions and rates) and binomial data. Available models are the flexible beta (Migliorati, S., Di Brisco, A. M., Ongaro, A. (2018) <doi:10.1214/17-BA1079>), the variance-inflated beta (Di Brisco, A. M., Migliorati, S., Ongaro, A. (2020) <doi:10.1177/1471082X18821213>), the beta (Ferrari, S.L.P., and Cribari-Neto, F. (2004) <doi:10.1080/0266476042000214501>), the flexible beta-binomial (Ascari, R. and Migliorati, S. (2021) <doi:10.1002/sim.9005>), the beta-binomial, and the binomial one. Inference is dealt with a Bayesian approach based on the Hamiltonian Monte Carlo (HMC) algorithm (Gelman, A.; Carlin, J. B.; Stern, H. S. and Rubin, D. B. (2014) <doi:10.1201/b16018>). Besides, functions to compute residuals, posterior predictives, goodness-of-fit measures, convergence diagnostics, and graphical representations are provided.

Roberto Ascari

FlexReg

Regression Models for Bounded Responses

Reading function

A data frame containing 44 observations on 3 variables.<dl>
<dt><code>accuracy</code></dt>
<dd>a reading score.</dd><dt><code>dyslexia</code></dt>
<dd>a factor indicating wheter the child is dyslexic.</dd><dt><code>iq</code></dt>
<dd>a quantitative measure of the children's non verbal abilities.</dd>
</dl>

Format

Reading Skills data — Reading

A data frame containing 44 observations on 3 variables.<dl>
<dt><code>accuracy</code></dt>
<dd>a reading score.</dd>

<dt><code>dyslexia</code></dt>
<dd>a factor indicating wheter the child is dyslexic.</dd>

<dt><code>iq</code></dt>
<dd>a quantitative measure of the children's non verbal abilities.</dd>


</dl>

Reading: Reading Skills data

Description

Arguments

Format

Details

References