View source: R/exp_score_codes.R
score_codes | R Documentation |
'Novel' and 'duplicate' codes are scored once per interview; the number of times they are spoken in an interview does not matter.
The definition of whether a code is novel or duplicated is entirely chronological:
A novel code is a topic/idea/concept that, for example, is mentioned in Interview 17, but was not mentioned in Interviews 1 through 16.
A duplicate code is one that has been talked about in other interviews previously.
The cumulative sum of novel codes is used to visualise a stopping point for qualitative interviews.
score_codes(interviews)
interviews |
(List) A list of dataframes, as generated by |
A dataframe, with one row per interview and these columns:
itvw_seq
, the chronological order of interviews.
n_codes
, the number of unique codes mentioned in this interview.
n_duplicate
, how many of those codes are duplicates mentioned in previous interviews).
n_novel
, how many of those codes are novel (mentioned for the first time in this interview).
prop_duplicate
, the proportion of this interview's codes that are duplicates.
prop_novel
, the proportion of this interview's codes that are novel.
cumsum_novel
, the cumulative sum of novel codes over time (i.e. across interviews).
plot_novelty()
, plot_richness()
# A folder of example coding matrices included with the package
path_to_matrices <- system.file("insect_study/matrices/", package = "novelqualcodes")
print(path_to_matrices)
# A list of files in that folder
list.files(path_to_matrices)
# Import them all at once
my_matrices <- import_coding_matrices(path_to_matrices)
# Score them for novel and duplicate codes
my_scores <- score_codes(my_matrices)
# Look inside the result; novel and duplicate codes are scored across
# all interviews.
print(my_scores)
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