quickly fits and plots psychometric functions for multiple groups
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README.md

quickpsy is an R package developed by Daniel Linares and Joan López-Moliner to quickly fit and plot psychometric functions for multiple conditions. It makes an extensive use of Hadley Wickham's packages ggplot2 and dplyr.

To understand the fundamentals of fitting psychometric functions in R, we recommend the book Modeling Psychophysical Data in R.

Features

  • Fits and plots multiple conditions with minimal coding.

  • Exploits the computational speed of dplyr.

  • The user does not need to introduce initial parameters.

  • Calculates parametric and non-parametric bootstrap confidence intervals.

  • Compares parameters and thresholds for different conditions using bootstrap.

  • Guess and lapses can be fixed or free as parameters.

  • Fits cumulative normal, logistic, weibull functions or any function defined by the user.

  • Facilitates the reading of several data files.

Install

Download and install R (we also recommend Rstudio).

In R, install the following packages: boot, DEoptim, dplyr, ggplot2, tidyr and devtools.

install.packages('boot')
install.packages('DEoptim')
install.packages('tidyr')
install.packages('devtools')

Quickpsy can be installed from CRAN

install.packages('quickpsy')

To install the latest developed version, you can install quickpsy from github (which will also install dplyr and ggplot2)

library(devtools)
install_github('danilinares/quickpsy')

Example

library(quickpsy)
library(MPDiR) # contains the Vernier data; use ?Venier for the reference

fit <- quickpsy(Vernier, Phaseshift, NumUpward, N, 
                grouping = .(Direction, WaveForm, TempFreq))
plotcurves(fit)

plots of vernier fits.

plotpar(fit) #plot the parameters

params of vernier fits

plotthresholds(fit)

thresholds of vernier fits

Help

To obtain information and examples for specific functions use ?

?plotcurves

For more examples and information visit www.dlinares.org/quickpsy.html

Other R packages