PAM_categorise: PAM_categorise
In studentlife: Tidy Handling and Navigation of the Student-Life Dataset

Description Usage Arguments Details Value References Examples

Categorise Photographic Affect Meter (PAM) scores into 4 categories by either PAM Quadrant, Valence or Arousal (or multiple of these).

PAM_categorise(
  tab,
  pam_name = "picture_idx",
  types = c("quadrant", "valence", "arousal")
)

`tab`	A data.frame (or tibble) with a column representing Photographic Affect Meter (PAM) score.
`pam_name`	Character. The name of the column representing PAM.
`types`	Character vector containing the categories, one or more of "quadrant", "valence" and "arousal" into which to code PAM scores.

The 4 Quadrant categories are as follows: Quadrant 1: negative valence, low arousal. Quadrant 2: negative valence, high arousal. Quadrant 3: positive valence, low arousal. Quadrant 4: positive valence, high arousal.

Valence and arousal are traditionally scores from -2 to 2, measuring displeasure to pleasure, and state of activation respectively. However, here we map those scores to positive numbers so (-2,-1,1,2) -> (1,2,3,4).

The data.frame (or tibble) tab with extra columns pam_q, pam_v, and pam_a for quadrant, valence and arousal respectively.

Pollak, J. P., Adams, P., & Gay, G. (2011, May). PAM: a photographic affect meter for frequent, in situ measurement of affect. In Proceedings of the SIGCHI conference on Human factors in computing systems (pp. 725-734). ACM.

d <- tempdir()
download_studentlife(location = d, url = "testdata")

tab <- load_SL_tibble(
  loc = d, schema = "EMA", table = "PAM", csv_nrows = 10)

PAM_categorise(tab)