View source: R/generate_crosswalk_table.R
generate_crosswalk_table | R Documentation |
Generate a crosswalk table for a list of instruments, given the similarity matrix that came out of the match function. A crosswalk is a list of pairs of variables from different studies that can be harmonised.
generate_crosswalk_table(
instruments,
similarity,
threshold,
is_allow_within_instrument_matches = FALSE,
is_enforce_one_to_one = FALSE
)
instruments |
The original list of instruments, each containing a question. The sum of the number of questions in all instruments is the total number of questions which should equal both the width and height of the similarity matrix. |
similarity |
The cosine similarity matrix from Harmony |
threshold |
The minimum threshold that we consider a match. This is applied to the absolute match value. So if a question pair has similarity 0.2 and threshold = 0.5, then that question pair will be excluded. Leave as None if you don't want to apply any thresholding. |
is_allow_within_instrument_matches |
Defaults to False. If this is set to True, we include crosswalk items that originate from the same instrument, which would otherwise be excluded by default. |
is_enforce_one_to_one |
Defaults to False. If this is set to True, we force all variables in the crosswalk table to be matched with exactly one other variable. |
A crosswalk table as a DataFrame.
Alex Nikic
instrument_A = create_instrument_from_list(list(
"How old are you?",
"What is your gender?"
))
instrument_B = create_instrument_from_list(list(
"Do you smoke?"
))
instruments = list(instrument_A, instrument_B)
match_response = match_instruments(instruments)
instrument_list = match_response$instruments
similarity_matrix = match_response$matches
crosswalk_table.df = generate_crosswalk_table(
instrument_list, similarity_matrix, threshold = 0.7,
is_allow_within_instrument_matches = FALSE, is_enforce_one_to_one = TRUE
)
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