Create treat_missing_values.R

[kouamea]

Aymone_snippets

[deflaux]

To elaborate further, people might want to handle NAs in different columns differently. For the example dataframe below:

• set all NAs in value_as_concept_id to zero for no matching concept and drop all rows
• suppose concept '42' means value was below detectable limit, the value_as_number in row 3 could be set to what ever the lowest detectable value is.
• and the fourth row should be dropped all together since both value_as_number and value_as_concept_id are NULL.

hba1c = data.frame(
  person_id = c(1, 2, 3, 4),
  value_as_number = c(5.5, 6.0, NA, NA),
  value_as_concept_id = c(NA, NA, 42, NA))

[deflaux]

closing old pull requests