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Package of data pipeline methods written for use in an image categorization task at the Sokol-Hessner Lab at University of Denver.

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shlab.imgct

The goal of shlab.imgct is to streamline the processing and analysis of participant category responses to blocks of images.

Installation

You can install the ongoing development version from GitHub with:

# install.packages("devtools")
devtools::install_github("sokolhessnerlab/shlab.imgct")

Example

This is a basic example which shows you how to solve a common problem:

library(shlab.imgct)

# Set your path to relevant task data
datapath <- "path/to/data"

# shlab.imgct::clean(datapath) # can be used as convenience
shlab.imgct::clean_qualtrics_export(datapath)

shlab.imgct::validate_all_participants(datapath)

shlab.imgct::categorize(datapath, threshold = 3)

shlab.imgct::analyze(datapath, "categorized_3_valid.tsv")

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Package of data pipeline methods written for use in an image categorization task at the Sokol-Hessner Lab at University of Denver.

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