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rater (development version)

rater 1.3.1

  • Fix the description of the number of raters in the anesthesia data. The documentation had erroneously stated there were four anesthetists, not five.

  • Update the stan code for compatibility with rstan v2.26.0 (@andrjohns)

rater 1.3.0

  • Updated the Stan implementation, priors, and initialisation points of the hierarchical Dawid-Skene model, leading to much more reliable convergence.

  • Added the ability to visualise the theta parameter with uncertainty.

  • Added row names to the output of class_probabilities().

  • Added the ability to specify the column names of long format data passed to rater().

  • Added simulate_dawid_skene_model() and simulate_hier_dawid_skene_model() to simulate data from the Dawid-Skene and hierarchical Dawid-Skene models.

  • Re-export loo_compare().

  • Allowed the theta parameter to be extracted from the hierarchical Dawid-Skene model.

rater 1.2.0

  • Add waic() function for model comparison

  • Silence warnings with the latest ggplot2 version

  • Fix validation bug in posterior_predict()

rater 1.1.0

  • summary() now works with the class conditional and hierarchical Dawid-Skene models.

  • All functions applied to fitted class conditional Dawid-Skene models will automatically convert the relevant parameters of the model into a full theta parameter equivalent to the Dawid-Skene model. This is designed to allow easier comparison of the class conditional model with the full Dawid-Skene model.

  • Plotting via plot() of the rater_fit object has been changed in several ways. plot.rater_fit now:

    • Only returns one plot
    • Only returns the theta plot by default
    • Exposes the prob, which (called rater_index) and new item_index arguments in the plot generic.

  • Add the ability to only plot a subset of items when plotting the class probabilities. This can be controlled by the new item_index argument to plot()

  • Added the function wide_to_long() to convert wide data to long data.

  • Add the option data_format = "wide" to rater() to allow wide data to be passed into rater() directly.

  • Added the get_stanfit() function to extract the underlying stanfit object from a rater fit object.

  • Added an implementation of the posterior_predict generic from {rstantools} allowing simulation from the posterior predictive distribution of fitted standard, and class conditional, Dawid-Skene models. (The hierarchical Dawid-Skene model is not yet supported).

  • Added an implementation of the prior_summary generic from {rstantools} for rater_fit objects.

  • Add the loo.rater_fit method to allow the calculation of loo, a modern Bayesian model comparison metric, for rater models. loo values can be compared using the excellent {loo} package.

  • Added the loo.rater_fit method to allow the calculation of loo, a modern Bayesian model comparison metric, for rater models. loo values can be compared using the excellent {loo} package.

  • Rater specific prior parameters can now be used in the Dawid-Skene model for both grouped and long data. In practice this means that it is now possible to pass a J * K * K array for beta into dawid_skene() which encodes a K * K prior parameter for each of the J raters' error matrices. For backwards compatibility and ease of use it is still possible to pass a single matrix for beta which will still be interpreted as the prior parameter for all the of the raters' error matrices.

  • The plot produced for the pi parameter has been changed. The new plot represents the uncertainty in the point estimates when MCMC has been used to fit the model.

  • Prior parameters for the Dawid-Skene and class conditional Dawid-Skene models have been altered slightly to improve convergence of optimization when the number of classes is small.

  • summary.mcmc_fit now displays the number of remaining parameters correctly.

  • Added the as_mcmc.list() function to convert MCMC fits to {coda} mcmc.list objects.

rater 1.0.0

  • Initial release