… True and Error model. Since our goal is to get the most out of our limited data, a hierarchical
model is … The one used in this paper shares the same cognitive model as defined previously, …

… participants have different true preferences or if different choice problems have different rates
of error. This paper reanalyzes their data using a true and error (TE) model, which does not …

… In this work, we introduce TRUE: a comprehensive survey and … point for model and metric
developers, and hope TRUE will … BLEURT includes additional pretraining on synthetic data …

… which true preferences could change within sessions. We used the true and error (TE) fitting
model to analyze the simulated data, … model satisfied the model assumptions, but also when …

… and interpreting model evaluation metrics, we analysed the responses of the True Skill Statistic
(… is the result of a four-part process that includes data collection, model training, threshold …

… In a set of 48 simulations, data generating models either … true preferences could change
within sessions. We used the true and error (TE) fitting model to analyze the simulated data, and …

… a numeric variable giving the data values and fa factor with TWO levels giving the corresponding
groups. data an optional matrix or data frame (or similar: see model. frame) containing …

… Consistent with this observation, we show that pseudo-true values do not in general
provide a satisfactory data summary for decision-makers whose loss depends on the …

… A simple alternative to logistic regression which will recover the desired direction in this
scenario is to take the vector pointing from the mean of the false data to the mean of the true data…

… true random-effects model to account for spatial dependence in persistent and transient
inefficiency. For this purpose, a model with … to let the data speak about the true parameter values. …