In rettopnivek/rtplots: Plotting functions for simple choice and response time data.

Introduction

This vignette provides a series of examples demonstrating how to use the 'rtplots' package. This package is most useful for quickly creating plots of response time distributions typically obtained in simple psychological experiments, particularly two-alternative forced-choice tasks.

Installation

The package can be installed via "devtools":

install.packages("devtools")
library(devtools)
install_github("rettopnivek/rtplots")

Once the package has been installed, we can load it for easy use:

library(rtplots)

Example data set

The 'rtplots' package includes response time and choice data for 25 subjects who completed a word identification task with immediate word priming. Subjects saw a fixation point, followed by a double presentation of prime word (vertically aligned) that could be shown either 50 or 400 ms. Immediately after, there was a brief flash (~50 ms) of the target word. The prime word could match the target, or it could be different (a lure). Subjects completed two tasks in alternating blocks. First, they completed a forced-choice two-alternative task in which the target and lure words were shown, and the subject had to identify the target word, irrespective of what the prime word had been. Second, subjects were shown a single word (either the target or the lure), and they had to indicate whether this word was the same or different compared to the target word. The following examples all involve this dataset.

# Load in example dataset
data("priming_data")
# For easy manipulation
d = priming_data

Base figures

Figures using the 'rtplots' package are made in two steps. First, the user creates a base figure, and second, the desired points and curves are added to this pre-existing figure. The package has a convenience function \code{blankRTplot} that can be used to quickly generate a base figure with standard labels.

Cumulative distribution curves

First, for clarity, we define a set of new variables for the vectors of response times and choice/accuracy values.

# Single subject
rt = d$RT[ d$Condition == 4 & d$Subject == 1 ]
# The package assumes that choice/accuracy is binary and 
# that values are coded as 0 or 1
ch = d$Accuracy[ d$Condition == 4 & d$Subject == 1 ]
print( unique(ch) )

We can then create a figure of the joint cumulative distribution functions for choice/accuracy values of 0 and 1 in three steps:

# Create a base figure
blankRTplot( 
  # Lower and upper boundary for time
  tDim = c( 0, 2 ),
  # Lower and upper boundary for probability
  pDim = c( 0, 1 ),
  # For joint cumulative distribution curves
  ver = "CDF",
  # Additional plotting parameters
  bty = 'n',
  cex.axis = 1.5,
  cex.lab = 1.5,
  lwd = 2
)

# Add CDF curve for choice/accuracy equal to 1
cdf_curve( 
  # Vectors for response times and choice/accuracy
  rt, ch, 
  # Additional plotting parameters
  lwd = 2 )

# Add CDF curve for choice/accuracy equal to 0
cdf_curve( 
  # Vectors for response times and choice/accuracy
  rt, ch,
  # For ch == 0
  sel = 0,
  # Additional plotting parameters
  lwd = 2,
  lty = 2 )

Vignettes are long form documentation commonly included in packages. Because they are part of the distribution of the package, they need to be as compact as possible. The html_vignette output type provides a custom style sheet (and tweaks some options) to ensure that the resulting html is as small as possible. The html_vignette format:

• Never uses retina figures
• Has a smaller default figure size
• Uses a custom CSS stylesheet instead of the default Twitter Bootstrap style

Vignette Info

Note the various macros within the vignette section of the metadata block above. These are required in order to instruct R how to build the vignette. Note that you should change the title field and the \VignetteIndexEntry to match the title of your vignette.

Styles

The html_vignette template includes a basic CSS theme. To override this theme you can specify your own CSS in the document metadata as follows:

output: 
  rmarkdown::html_vignette:
    css: mystyles.css

Figures

The figure sizes have been customised so that you can easily put two images side-by-side.

plot(1:10)
plot(10:1)

You can enable figure captions by fig_caption: yes in YAML:

output:
  rmarkdown::html_vignette:
    fig_caption: yes

Then you can use the chunk option fig.cap = "Your figure caption." in knitr.

More Examples

You can write math expressions, e.g. $Y = X\beta + \epsilon$, footnotes^[A footnote here.], and tables, e.g. using knitr::kable().

knitr::kable(head(mtcars, 10))

Also a quote using >:

"He who gives up [code] safety for [code] speed deserves neither." (via)

rettopnivek/rtplots documentation built on May 27, 2019, 5:55 a.m.