In multivariable GLMM it is no longer necessary to put the continuous predictor in the first position in the formula object in order to estimate the JND and PSE via `MERtreatment()`

. See `MERdemo()`

for a working example.

## Bug fix #070815

## Easy fit of psychometric functions

Using `psych.function`

you can fit the data of the single participant (via call of standard `glm`

function), estimate JND and PSE via delta method and plot the model predictions. The names of the Arguments are consistent with standard `glm`

and `lines`

function preceded by “ps.”; example ps.formula, pd.data, ps.col, etc. For the moment only works for univariable psychometric functions (lazy Italians…). See MERdemo.R and the on line tutorial for details. Write me for feedback/suggestions! ðŸ™‚

## Beep sound when bootstrap is finished

just a small change: In the pseMer function now you can set beep = T to play an alert sound when the bootstrap is finished. You need to install the package beepr to use this option. Thanks to Rasmus Baath, the author and maintainer of the package for this nice tool.

## MERpsychophysics.0

This is the old version of the package, compatible with lme4.0. It is possible to estimate the PSE and JND of a GLMM with having single, fixed-effed categolical predictor. The estimate is performed either via delta method or with a parametric bootstrap. The function for the parametric bootstrap (MERboot) samples the random predictor from a univariate or bivariate normal distribution using the package mnorm. The algorithms are described in Moscatelli et al. (2012).

## MERpsychophysics1.1

This package version is compatible with lme4.1. It allows the estimate of PSE and JND via delta method or bootstrap. The current bootstrap function is based on bootMer{lme4.1}. The algorithm is similar to my previous function MERboot{MERpsychophysics.0}, which is referenced in Moscatelli et al. (2012).

GLMMplot can be used for plotting, while the analougus function MERplot is not ready yet. The user manual is forthcoming – for now, see the MERdemo.R file for help.