normalize_scores_grouped {stenR} | R Documentation |
Normalize scores using GroupedFrequencyTables or GroupedScoreTables
Description
Normalize scores using either GroupedFrequencyTable
or
GroupedScoreTable
for one or more variables. Given data.frame should also
contain columns used in GroupingConditions
attached to the table
Usage
normalize_scores_grouped(
data,
vars,
...,
what,
retain = FALSE,
group_col = NULL,
.dots = list()
)
Arguments
data |
data.frame object containing raw scores |
vars |
names of columns to normalize. Length of vars
need to be the same as number of tables provided to either |
... |
|
what |
the values to get. One of either:
|
retain |
either boolean: |
group_col |
name of the column for name of the group each
observation was qualified into. If left as default |
.dots |
|
Value
data.frame with normalized scores
See Also
Other score-normalization functions:
normalize_scores_df()
,
normalize_scores_scoring()
,
normalize_score()
Examples
# setup - create necessary objects #
suppressMessages({
age_grouping <- GroupConditions(
conditions_category = "Age",
"below 22" ~ age < 22,
"23-60" ~ age >= 23 & age <= 60,
"above 60" ~ age > 60
)
sex_grouping <- GroupConditions(
conditions_category = "Sex",
"Male" ~ sex == "M",
"Female" ~ sex == "F"
)
NEU_gft <- GroupedFrequencyTable(
data = IPIP_NEO_300,
conditions = list(age_grouping, sex_grouping),
var = "N"
)
NEU_gst <- GroupedScoreTable(
NEU_gft,
scale = list(STEN, STANINE)
)
})
#### normalize scores ####
# to Z score or quantile using GroupedFrequencyTable
normalized_to_quan <- normalize_scores_grouped(
IPIP_NEO_300,
vars = "N",
NEU_gft,
what = "quan",
retain = c("sex", "age")
)
# only 'sex' and 'age' are retained
head(normalized_to_quan)
# to StandardScale attached to GroupedScoreTable
normalized_to_STEN <- normalize_scores_grouped(
IPIP_NEO_300,
vars = "N",
NEU_gst,
what = "stanine",
retain = FALSE,
group_col = "sex_age_group"
)
# none is retained, 'sex_age_group' is created
head(normalized_to_STEN)