clinpubr (version 1.1.1)

get_valid_subset: Get the subset that satisfies the missing rate condition.

Description

Get the subset of a data frame that satisfies the missing rate condition using a greedy algorithm.

Usage

get_valid_subset(
  df,
  row_na_ratio = 0.5,
  col_na_ratio = 0.2,
  row_priority = 1,
  speedup_ratio = 0,
  return_index = FALSE
)

Value

The subset data frame, or a list that contains the row and column indices of the subset.

Arguments

df

A data frame.

row_na_ratio

The maximum acceptable missing rate of rows.

col_na_ratio

The maximum acceptable missing rate of columns.

row_priority

A positive numerical, the priority to keep rows. The higher the value, the higher the priority, with 1 indicating equal priority for rows and columns.

speedup_ratio

A positive numerical, the ratio of speedup. The higher the value, the greedier the algorithm. Should be in range of [0, 1].

return_index

A logical, whether to return only the row and column indices of the subset.

Details

The function is based on a greedy algorithm. It iteratively removes the row or column with the highest excessive missing rate weighted by the inverse of row_priority until the missing rates of all rows and columns are below the specified threshold. Then it reversely tries to add rows and columns that do not break the conditions back and finalize the subset. The result depends on the row_priority parameter drastically, so it's recommended to try different row_priority values to find the most satisfying one.

Examples

data(cancer, package = "survival")
dim(cancer)
max_missing_rates(cancer)

cancer_valid <- get_valid_subset(cancer, row_na_ratio = 0.2, col_na_ratio = 0.1, row_priority = 1)
dim(cancer_valid)
max_missing_rates(cancer_valid)