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Fills missing values with subgroup mean value

impute_mean.Rd

Replaces any values < 0 with NA, calculates the subgroup mean, then replaces missing values with the subgroup mean.

Usage

impute_mean(
  data,
  var_names,
  remove_zeros = FALSE,
  strat_vars = c("year", "sex", "imd_quintile", "age_cat")
)

Arguments

data

Data table - the health survey data

var_names

Character vector - the variable names to be imputed (numeric variables only)

remove_zeros

Logical - should zeros be treated as missing data

strat_vars

Character vector - the variables by which to stratify the subgroup means

Value

Returns an updated version of data in which the variables specified have had their missing values imputed with the subgroup means.

Details

If not all NAs can be imputed with the fine scale starting amount of stratification, imputation is attempted again, removing the stratification variable specified last.

Examples


if (FALSE) { # \dontrun{

data <- read_2001()
data <- clean_age(data)
data <- clean_demographic(data)
data <- impute_mean(data, var_names = c("d7many"))

} # }