post_clean_chance: Scrub processed data with below-chance accuracy

In josegallegos07/aceR: Tools for processing ACE data

Scrub processed data with below-chance accuracy

Description

User-friendly wrapper to replace below-chance records with NA in ACE data processed with proc_by_module. Currently only compatible with ACE (SEA not yet implemented),

Usage

post_clean_chance(
  df,
  app_type = c("classroom", "explorer"),
  overall = TRUE,
  cutoff_dprime = 0,
  cutoff_2choice = 0.5,
  cutoff_4choice = 0.25,
  cutoff_5choice = 0.2,
  cutoff_k = 1,
  extra_demos = NULL
)

Arguments

df	a df, output by proc_by_module, containing processed ACE data.
app_type	character. What app type produced this data? One of c("classroom", "explorer"). Must be specified.
overall	Also scrub ".overall" data? Defaults to TRUE.
cutoff_dprime	Maximum value of d' to replace with NA, for relevant tasks (ACE Tap and Trace, SAAT). Defaults to 0.
cutoff_2choice	Maximum value of accuracy to replace with NA, for 2-response tasks (ACE Flanker, Boxed). Defaults to 0.5.
cutoff_4choice	Maximum value of accuracy to replace with NA, for 4-response tasks (ACE Stroop, Task Switch). Defaults to 0.25.
cutoff_5choice	Maximum value of accuracy to replace with NA, for 5-response tasks (ACE Color Selection). Defaults to 0.2.
cutoff_k	Maximum relative value of Filter k to replace with NA. Defaults to 1, which corresponds to 1 target item in both 2-target conditions and 4-target conditions.
extra_demos	Character vector specifying any custom-added demographics columns (beyond app defaults) to pass through the function. Defaults to {codeNULL.

Value

a df, similar in structure to proc, but with below-cutoff values in certain columns converted to NA.

josegallegos07/aceR documentation built on June 27, 2022, 10:25 a.m.