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prolific academic provides a demographics file. This reads it and merges with your data using PID and participant_id
umx_read_prolific_demog(
file,
base = "",
df = NULL,
verbose = FALSE,
by.df = "PID",
by.demog = "participant_id",
vars = c("age", "Sex"),
all.df = TRUE,
all.demog = FALSE
)
Path to a file to read.
Optional path to folder
Optional existing datafile
Whether to print names in the file.
The ID name in your datafile (default = "PID")
The ID name in the prolific demographics file (default = "participant_id")
Vars to keep from demographics file (default = age & Sex)
Whether to keep all lines of df (default = TRUE)
Whether to keep all lines (people) in the demographics file (default = FALSE)
Other Data Functions:
umxFactor()
,
umxHetCor()
,
umx_as_numeric()
,
umx_cont_2_quantiles()
,
umx_lower2full()
,
umx_make_MR_data()
,
umx_make_TwinData()
,
umx_make_fake_data()
,
umx_make_raw_from_cov()
,
umx_polychoric()
,
umx_polypairwise()
,
umx_polytriowise()
,
umx_read_lower()
,
umx_rename()
,
umx_reorder()
,
umx_score_scale()
,
umx_select_valid()
,
umx_stack()
,
umx
# NOT RUN {
fp = "~/Desktop/prolific_export_5f20c3e662e3b6407dcd37a5.csv"
df = umx_read_prolific_demog(fp, df = df)
tmp = umx_read_prolific_demog(demog= fp, base = "", df = NULL, verbose = FALSE)
# }
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