LexOPS

LexOPS is an R package for generating matched stimuli for factorial design experiments. You can use the functions on any dataframe, but there is an inbuilt database of example features for English words for psycholinguistics studies in English (LexOPS::lexops).

Installation

LexOPS can be installed as an R package with:

if (!require("devtools")) install.packages("devtools")
devtools::install_github("JackEdTaylor/LexOPS@*release")

How to Use

📖 In-depth walkthrough of the package: https://jackedtaylor.github.io/LexOPSdocs/

🎓 Paper about the package: Taylor, Beith, and Sereno (2020)

TL;DR

LexOPS makes it easy to generate matched stimuli in a reproducible way.

The “Generate Pipeline”

The following example pipeline generates 50 words (all nouns) per condition (200 words in total), for a study with a 2 x 2, concreteness (low, high) by bigram probability (low, high) experimental design. Words are controlled for by length exactly, and by word frequency within a tolerance of ±0.2 Zipf.

library(LexOPS)

# generate stimuli
stim <- lexops %>%
  subset(PoS.SUBTLEX_UK == "noun") %>%
  split_by(BG.SUBTLEX_UK, 0.001:0.004 ~ 0.008:0.011) %>%
  split_by(CNC.Brysbaert, 1:2 ~ 4:5) %>%
  control_for(Zipf.SUBTLEX_UK, -0.2:0.2) %>%
  control_for(Length) %>%
  generate(n = 50, match_null = "balanced")

#> Generated 5/50 (10%). 6 total iterations, 0.83 success rate.
#> Generated 10/50 (20%). 12 total iterations, 0.83 success rate.
#> Generated 15/50 (30%). 19 total iterations, 0.79 success rate.
#> Generated 20/50 (40%). 27 total iterations, 0.74 success rate.
#> Generated 25/50 (50%). 39 total iterations, 0.64 success rate.
#> Generated 30/50 (60%). 46 total iterations, 0.65 success rate.
#> Generated 35/50 (70%). 52 total iterations, 0.67 success rate.
#> Generated 40/50 (80%). 84 total iterations, 0.48 success rate.
#> Generated 45/50 (90%). 100 total iterations, 0.45 success rate.
#> Generated 50/50 (100%). 117 total iterations, 0.43 success rate.

A preview of what was generated:

# create a table of the first 20 words (4 per row) as an example
stim %>%
  head(5) %>%
  knitr::kable()

Review Generated Stimuli

The plot_design() function produces a plot summarising the generated stimuli.

plot_design(stim)

Convert to Long Format

The long_format() function coerces the generated stimuli into long format.

# present the same 20 words as in the last table
long_format(stim) %>%
  head(20) %>%
  knitr::kable()

Shiny App

The package has an interactive shiny app, which supports most code functionality, with useful additional features like visualising distributions and relationships. It’s a friendly front-end to the package’s functions. A demo version of the LexOPS shiny app is available online at https://jackt.shinyapps.io/lexops/, but it is faster and more reliable to run it locally, with:

LexOPS::run_shiny()