normalize_scores_grouped: Normalize scores using GroupedFrequencyTables or...

In StatisMike/stenR: Standardization of Raw Discrete Questionnaire Scores

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 ... or .dots
...	GroupedFrequencyTable or GroupedScoreTable objects to be used for normalization. They should be provided in the same order as vars
what	the values to get. One of either: quan - the quantile of x in the raw score distribution Z - normalized Z score for the x raw score name of the scale calculated in GroupedScoreTables provided to ... or .dots argument
retain	either boolean: TRUE if all columns in the data are to be retained, FALSE if none; or character vector with names of columns to be retained
group_col	name of the column for name of the group each observation was qualified into. If left as default NULL, they won't be returned.
.dots	GroupedFrequencyTable or GroupedScoreTable objects provided as a list, instead of individually in ....

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)

StatisMike/stenR documentation built on Aug. 20, 2022, 9:30 a.m.