The goal of mturkr
is to easily and quickly create the the batch data
set needed to send back to Amazon Mechanical Turk. This package will
create a new data set with the required reject and approve columns to
for participants payment.
I use MTurk a lot for my data collection so I think it is worthwhile to create a package of the functions so that my analysis is cleaner. I mainly intend to use this myself but if you use MTurk for data collection as well, you might find this package useful
You can install the development version of mturkr
from
GitHub with:
# install.packages("devtools")
devtools::install_github("andr3wli/mturkr")
This is how you would use the functions in the :
# read in the data
batch <- readr::read_csv("data/exp6/Batch_4646160_batch_results.csv")
mturk <- readr::read_csv("data/exp6/mturkcode.csv")
analysis <- readr::read_csv("data/exp6/petition.csv")
library(mturkr)
# See if the batch code participants gave matches the mturk code we provided
keep <- discard_list(df1 = batch, df2 = mturk)
# check if participants passed the attention check
# note the example data set in this package did not have an attention check
attention_question <- "This is an attention check. Please select ‘strongly agree’ to pass this check. You will not be compensated if you fail this check."
failed <- failed_attention_check(analysis, question = attention_question)
# create the approve column
clean_batch <- create_approve_col(batch, keep = keep, fail = failed)
# create the reject column
clean_batch <- create_reject_col(clean_batch, keep = keep, fail = failed)
# finally, save the new data set to be sent back to Amazon to confirm which participants get payment
readr::write_csv(clean_batch, file = here::here("clean_batch", "batch_data_payment_confirmation.csv"))
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