library(dplyr)
library(purrr)
library(tidyr)
library(ggplot2)
library(hash)QUALTRICS_FILENAME = "qualtrics.tsv"Begin by setting the working directory and important top-level paths to data and loading necessary packages.
- NOTE: This will be changed to dynamically account for the package
shlab.imgctvia its GitHub instance later. For now, it is using development loading.
# Set the working directory to be part of S Drive (may make dynamic later?)
# Whilst not dynamic, change for own session if mount point is not equivalent on
# local machine
shared_dir <- "~/Projects/shlab/mounts/imgct"
package_dir <- "~/Projects/shlab"
datapath <- file.path(shared_dir, "csn_images")
imgct_package_path <- file.path(package_dir, "shlab.imgct")
# Make sure that devtools, tidyverse are installed before this call
devtools::load_all(imgct_package_path)Using the convience method shlab.imgct::load_qualtrics_tsv will load a
TSV export of Qualtrics response data collected from the image
categorization task. (Please note that the output of this raw dataset is
hidden to maintain participant privacy.)
qualtrics_export <- shlab.imgct::load_qualtrics_tsv(datapath)Remove unnecessary columns of data from the Qualtrics exported data, and remove participant rows in which the task was not complete. The output of this function will show the first five participants.
qualtrics_export_parsed <- shlab.imgct::parse_qualtrics_export(qualtrics_export)
knitr::kable(head(qualtrics_export_parsed, 5))| participant_id | imageBlock | X1_Q10 | X2_Q10 | X3_Q10 | X4_Q10 | X5_Q10 | X6_Q10 | X7_Q10 | X8_Q10 | X9_Q10 | X10_Q10 | X11_Q10 | X12_Q10 | X13_Q10 | X14_Q10 | X15_Q10 | X16_Q10 | X17_Q10 | X18_Q10 | X19_Q10 | X20_Q10 | X21_Q10 | X22_Q10 | X23_Q10 | X24_Q10 | X25_Q10 | X26_Q10 | X27_Q10 | X28_Q10 | X29_Q10 | X30_Q10 | X31_Q10 | X32_Q10 | X33_Q10 | X34_Q10 | X35_Q10 | X36_Q10 | X37_Q10 | X38_Q10 | X39_Q10 | X40_Q10 | X41_Q10 | X42_Q10 | X43_Q10 | X44_Q10 | X45_Q10 | X46_Q10 | X47_Q10 | X48_Q10 | X49_Q10 | X50_Q10 | X51_Q10 | X52_Q10 | X53_Q10 | X54_Q10 | X55_Q10 | X56_Q10 | X57_Q10 | X58_Q10 | X59_Q10 | X60_Q10 | X61_Q10 | X62_Q10 | X63_Q10 | X64_Q10 | X65_Q10 | X66_Q10 | X67_Q10 | X68_Q10 | X69_Q10 | X70_Q10 | X71_Q10 | X72_Q10 | X73_Q10 | X74_Q10 | X75_Q10 | X76_Q10 | X77_Q10 | X78_Q10 | X79_Q10 | X80_Q10 | X81_Q10 | X82_Q10 | X83_Q10 | X84_Q10 | X85_Q10 | X86_Q10 | X87_Q10 | X88_Q10 | X89_Q10 | X90_Q10 | X91_Q10 | X92_Q10 | X93_Q10 | X94_Q10 | X95_Q10 | X96_Q10 | X97_Q10 | X98_Q10 | X99_Q10 | X100_Q10 | X101_Q10 | X102_Q10 | X103_Q10 | X104_Q10 | X105_Q10 | X106_Q10 | X107_Q10 | X108_Q10 | X109_Q10 | X110_Q10 | X111_Q10 | X112_Q10 | X113_Q10 | X114_Q10 | X115_Q10 | X116_Q10 | X117_Q10 | X118_Q10 | X119_Q10 | X120_Q10 | X121_Q10 | X122_Q10 | X123_Q10 | X124_Q10 | X125_Q10 | X126_Q10 | X127_Q10 | X128_Q10 | X129_Q10 | X130_Q10 | X131_Q10 | X132_Q10 | X133_Q10 | X134_Q10 | X135_Q10 | X136_Q10 | X137_Q10 | X138_Q10 | X139_Q10 | X140_Q10 | X141_Q10 | X142_Q10 | X143_Q10 | X144_Q10 | X145_Q10 | X146_Q10 | X147_Q10 | X148_Q10 | X149_Q10 | X150_Q10 | X151_Q10 | X152_Q10 | X153_Q10 | X154_Q10 | X155_Q10 | X156_Q10 | X157_Q10 | X158_Q10 | X159_Q10 | X160_Q10 | X161_Q10 | X162_Q10 | X163_Q10 | X164_Q10 | X165_Q10 | X166_Q10 | X167_Q10 | X168_Q10 | X169_Q10 | X170_Q10 | X171_Q10 | X172_Q10 | X173_Q10 | X174_Q10 | X175_Q10 | X176_Q10 | X177_Q10 | X178_Q10 | X179_Q10 | X180_Q10 | X181_Q10 | X182_Q10 | X183_Q10 | X184_Q10 | X185_Q10 | X186_Q10 | X187_Q10 | X188_Q10 | X189_Q10 | X190_Q10 | X191_Q10 | X192_Q10 | X193_Q10 | X194_Q10 | X195_Q10 | X196_Q10 | X197_Q10 | X198_Q10 | X199_Q10 | X200_Q10 | X201_Q10 | X202_Q10 | X203_Q10 | X204_Q10 | X205_Q10 |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| ICT_001 | 01 | 1 | 5 | 4 | 4 | 1 | 3 | 1 | 1 | 1 | 1 | 3 | 5 | 1 | 1 | 2 | 1 | 1 | 4 | 1 | 2 | 1 | 1 | 2 | 1 | 1 | 1 | 2 | 1 | 2 | 2 | 1 | 3 | 3 | 3 | 2 | 3 | 2 | 1 | 3 | 1 | 1 | 1 | 2 | 3 | 4 | 2 | 3 | 5 | 3 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 4 | 4 | 4 | 2 | 4 | 3 | 4 | 1 | 5 | 5 | 2 | 2 | 1 | 3 | 3 | 3 | 1 | 4 | 1 | 1 | 2 | 3 | 1 | 3 | 4 | 3 | 1 | 1 | 3 | 2 | 4 | 1 | 4 | 4 | 4 | 1 | 3 | 2 | 5 | 1 | 1 | 3 | 1 | 4 | 1 | 1 | 1 | 1 | 3 | 4 | 3 | 1 | 2 | 2 | 1 | 4 | 3 | 1 | 1 | 5 | 3 | 2 | 1 | 3 | 1 | 4 | 3 | 3 | 1 | 1 | 1 | 4 | 1 | 4 | 3 | 4 | 1 | 1 | 4 | 1 | 1 | 4 | 4 | 3 | 1 | 3 | 2 | 2 | 3 | 1 | 3 | 2 | 3 | 1 | 1 | 4 | 1 | 3 | 1 | 1 | 1 | 2 | 3 | 1 | 1 | 4 | 2 | 3 | 1 | 1 | 1 | 4 | 2 | 1 | 1 | 1 | 1 | 4 | 1 | 1 | 1 | 4 | 2 | 3 | 2 | 4 | 4 | 2 | 5 | 1 | 1 | 5 | 4 | 1 | 4 | 3 | 1 | 1 | 1 | 1 | 3 | 1 | 5 | 3 | 3 | 2 | 1 | 4 | 4 |
| ICT_002 | 01 | 1 | 3 | 3 | 3 | 3 | 3 | 1 | 1 | 1 | 1 | 4 | 3 | 1 | 1 | 1 | 1 | 1 | 4 | 4 | 4 | 2 | 1 | 5 | 1 | 1 | 1 | 2 | 2 | 2 | 2 | 3 | 3 | 3 | 1 | 2 | 3 | 2 | 1 | 3 | 1 | 1 | 1 | 1 | 1 | 3 | 2 | 4 | 4 | 4 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 2 | 1 | 2 | 4 | 4 | 4 | 1 | 4 | 2 | 2 | 1 | 1 | 4 | 4 | 3 | 1 | 4 | 1 | 1 | 2 | 3 | 1 | 3 | 1 | 3 | 1 | 1 | 1 | 2 | 4 | 1 | 1 | 4 | 4 | 1 | 4 | 3 | 4 | 1 | 1 | 4 | 1 | 4 | 1 | 1 | 1 | 1 | 1 | 4 | 3 | 2 | 2 | 2 | 1 | 1 | 3 | 1 | 1 | 3 | 3 | 2 | 1 | 3 | 1 | 1 | 1 | 4 | 1 | 1 | 1 | 3 | 1 | 1 | 4 | 4 | 1 | 1 | 4 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 2 | 2 | 1 | 1 | 3 | 2 | 1 | 1 | 2 | 1 | 3 | 2 | 1 | 1 | 1 | 2 | 3 | 1 | 3 | 1 | 1 | 4 | 3 | 1 | 1 | 1 | 1 | 2 | 3 | 1 | 4 | 2 | 3 | 4 | 4 | 4 | 4 | 3 | 2 | 4 | 4 | 2 | 1 | 1 | 1 | 1 | 1 | 2 | 2 | 4 | 1 | 3 | 4 | 4 | 3 | 1 | 5 | 2 | 1 | 3 | 1 | 2 | 3 |
| ICT_003 | 01 | 1 | 5 | 4 | 3 | 1 | 3 | 1 | 1 | 1 | 1 | 3 | 3 | 1 | 1 | 2 | 1 | 1 | 4 | 1 | 2 | 1 | 1 | 2 | 1 | 1 | 1 | 2 | 1 | 2 | 2 | 1 | 3 | 3 | 1 | 2 | 3 | 2 | 1 | 3 | 1 | 1 | 1 | 1 | 3 | 4 | 2 | 4 | 4 | 3 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 2 | 1 | 2 | 4 | 4 | 4 | 1 | 4 | 4 | 2 | 2 | 1 | 4 | 3 | 3 | 1 | 4 | 1 | 1 | 2 | 3 | 1 | 3 | 1 | 3 | 1 | 1 | 1 | 2 | 4 | 1 | 1 | 3 | 4 | 4 | 2 | 4 | 1 | 1 | 4 | 1 | 4 | 1 | 1 | 1 | 1 | 3 | 4 | 3 | 2 | 2 | 2 | 1 | 1 | 3 | 1 | 1 | 1 | 3 | 2 | 1 | 3 | 1 | 1 | 1 | 4 | 1 | 1 | 1 | 2 | 1 | 4 | 4 | 1 | 1 | 1 | 4 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 2 | 2 | 3 | 1 | 3 | 2 | 1 | 1 | 1 | 1 | 1 | 3 | 1 | 1 | 1 | 3 | 3 | 1 | 1 | 4 | 2 | 3 | 1 | 1 | 1 | 4 | 2 | 1 | 1 | 1 | 1 | 4 | 1 | 1 | 1 | 4 | 3 | 3 | 2 | 4 | 4 | 2 | 1 | 1 | 1 | 1 | 4 | 1 | 1 | 3 | 1 | 1 | 1 | 1 | 3 | 1 | 5 | 3 | 3 | 2 | 1 | 4 | 4 | |
| ICT_004 | 01 | 1 | 3 | 3 | 3 | 1 | 3 | 1 | 1 | 1 | 1 | 3 | 4 | 1 | 1 | 2 | 1 | 1 | 4 | 1 | 2 | 1 | 1 | 3 | 1 | 1 | 1 | 2 | 1 | 2 | 2 | 1 | 3 | 4 | 3 | 2 | 3 | 2 | 1 | 3 | 1 | 1 | 1 | 1 | 3 | 3 | 2 | 3 | 4 | 3 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 2 | 1 | 2 | 4 | 3 | 4 | 1 | 3 | 2 | 2 | 2 | 1 | 4 | 3 | 3 | 1 | 4 | 1 | 1 | 2 | 3 | 1 | 3 | 1 | 3 | 1 | 1 | 3 | 2 | 4 | 1 | 1 | 3 | 4 | 1 | 4 | 2 | 4 | 1 | 1 | 4 | 1 | 4 | 1 | 1 | 1 | 1 | 3 | 4 | 3 | 2 | 2 | 2 | 1 | 4 | 3 | 1 | 1 | 1 | 3 | 2 | 1 | 3 | 1 | 1 | 3 | 4 | 1 | 1 | 1 | 3 | 1 | 3 | 4 | 1 | 1 | 1 | 4 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 2 | 2 | 3 | 1 | 3 | 2 | 3 | 1 | 1 | 1 | 1 | 3 | 1 | 1 | 1 | 2 | 3 | 1 | 1 | 4 | 2 | 3 | 1 | 1 | 1 | 4 | 2 | 1 | 1 | 1 | 1 | 4 | 1 | 1 | 1 | 4 | 2 | 3 | 2 | 4 | 4 | 2 | 1 | 1 | 1 | 1 | 4 | 1 | 1 | 3 | 1 | 1 | 1 | 3 | 3 | 1 | 5 | 3 | 5 | 2 | 1 | 4 | 4 |
| ICT_005 | 01 | 1 | 3 | 4 | 3 | 1 | 3 | 1 | 1 | 1 | 1 | 3 | 4 | 1 | 1 | 2 | 1 | 1 | 3 | 1 | 2 | 1 | 1 | 3 | 1 | 1 | 1 | 2 | 1 | 2 | 2 | 1 | 4 | 3 | 1 | 2 | 3 | 2 | 1 | 3 | 1 | 1 | 1 | 1 | 3 | 3 | 2 | 3 | 4 | 3 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 4 | 1 | 2 | 4 | 4 | 4 | 1 | 4 | 4 | 2 | 2 | 1 | 3 | 3 | 3 | 1 | 4 | 1 | 1 | 2 | 3 | 1 | 3 | 1 | 3 | 1 | 1 | 3 | 2 | 4 | 1 | 1 | 4 | 4 | 1 | 3 | 3 | 4 | 1 | 1 | 4 | 1 | 4 | 1 | 1 | 1 | 1 | 1 | 4 | 3 | 2 | 2 | 2 | 1 | 1 | 3 | 4 | 1 | 4 | 3 | 2 | 1 | 3 | 1 | 4 | 3 | 4 | 1 | 1 | 1 | 4 | 1 | 4 | 4 | 4 | 1 | 1 | 4 | 3 | 1 | 4 | 1 | 1 | 1 | 1 | 2 | 2 | 1 | 1 | 3 | 2 | 1 | 1 | 1 | 4 | 1 | 3 | 1 | 4 | 1 | 2 | 3 | 1 | 1 | 4 | 2 | 3 | 1 | 1 | 1 | 4 | 2 | 1 | 1 | 1 | 1 | 4 | 1 | 1 | 1 | 4 | 2 | 3 | 2 | 4 | 4 | 2 | 1 | 1 | 1 | 1 | 4 | 1 | 4 | 3 | 1 | 1 | 1 | 1 | 3 | 1 | 5 | 4 | 3 | 2 | 1 | 4 | 4 |
The two above demonstrations are included within the function to clean
Qualtrics exported survey data for this task. Additionally, the clean
function is a convenience on top of clean_qualtrics_export that
(currently) only allows for Qualtrics TSV response data. Within the
call, TXT files of each image block are loaded to rename columns for
each block of image categorization rating responses, as Qualtrics also
unfortunately replaces columns with each block of images surveyed.
# Here, we demonstrate the underlying Qualtrics-specific method
shlab.imgct::clean_qualtrics_export(datapath, filename = QUALTRICS_FILENAME)Using the convenient abstraction clean, we can load, parse, and clean
each block of image categorization rating responses across participants.
This will, notably, remove any participant that that has errors in their
responses, too. If successful, the cleaned blocks will be saved to the
~/datapath/clean directory.
shlab.imgct::clean(datapath, filename = QUALTRICS_FILENAME)## [1] "Success! Your clean blocks were saved to ~/Projects/shlab/mounts/imgct/csn_images/clean"