find_missing.Rdfind_missing is a function that identifies which rows have missing covariate values and which covariates are missing from any row.
find_missing(data, models = NULL, covariates = NULL, ...)Source data
A model_specification object. If passed, the function will find missingness for all variables in all specified models.
Variables to check for missingness. If a model specification object is passed, this parameter is ignored.
Optional arguments to find_missing (not currently used).
A named list with class missingness with entries containing
information about the rows and columns with missingness. Each of the
entries is with respect to a set of covariates that are determined either
by the set of columns in data that are included in at least one of the
models in models or by the value of covariates (models takes
precedence if both are provided). The elements in the return value are the
following:
missing_covs: a character vector of the covariates with missing values
in them
missing_indicator: a numeric vector of 0s and 1s of length given by the
number of rows in data. A value of 0 in the k-th element indicates
that none of the k-th values in any of the covariates are missing,
while a value of 1 in the k-th element indicates that the k-th value
for at least one of the covariates is missing
missing_data: a logical matrix with dimensions n * q where n is the
number of rows in data and q is the number of covariates under
consideration. Each column in the matrix is the result that would be
obtained by invoking is.na on the column with the same name from the
object that was provided as the input to the data argument