impute_missing_score: Impute for Missing Values

In NeuroShepherd/RankinLabTools: General data cleaning tools for the Rankin lab

Impute for Missing Values

Description

This function calculates imputed scores where item-level data is missing, and allows for the threshold of proportion of missing questions to be adjusted

Usage

impute_missing_score(
  .data,
  vars_to_impute,
  scale_name,
  missing_threshold = 0.2
)

Arguments

.data	A data frame, data frame extension (e.g. a tibble), or a lazy data frame (e.g. from dbplyr or dtplyr).
vars_to_impute	vector of variables from which a score will be calculated/imputed
scale_name	output name of the scale being calculated
missing_threshold	maximum proportion of the scale questions allowed to be missing (i.e. the scale will not be calculated if the number of missing questions is greater than this value)
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NeuroShepherd/RankinLabTools documentation built on Sept. 23, 2022, 5:31 p.m.