Convert PDQ responses to a trial-level choice frame

Reshapes long-form Probability Discounting Questionnaire (PDQ) responses into a per-trial certain-versus-risky choice frame, joining each questionid to the canonical item design (certain amount, probabilistic amount, probability, and odds against theta = (1 - p)/p) from Madden, Petry, & Johnson (2009; see get_lookup_table()).

Usage

pdq_to_choice(
  responses,
  id_var = "subjectid",
  question_var = "questionid",
  response_var = "response"
)

Arguments

responses

Long-form data frame with one row per PDQ item per subject, holding the columns named by id_var, question_var, and response_var. response is 0 for the smaller guaranteed reward and 1 for the larger risky reward.

id_var, question_var, response_var

Column names in responses for the subject id, PDQ question id (1-30), and the binary choice. Defaults match the bundled pdq dataset ("subjectid", "questionid", "response").

Value

A tibble with columns id (character), sc_amount, lu_amount, prob, theta (odds against winning), and choice (0/1, 1 = chose the risky reward), in the input row order.

Details

Unknown or non-coercible question ids raise an error rather than silently producing unmatched rows. Ragged input is allowed (subjects need not have all items) and NA responses are preserved. For the strict scorer see score_pdq().

See also

score_pdq(), get_lookup_table(), mcq_to_choice()

Examples

ch <- pdq_to_choice(pdq)
head(ch)
#> # A tibble: 6 × 6
#>   id    sc_amount lu_amount  prob theta choice
#>   <chr>     <dbl>     <dbl> <dbl> <dbl>  <dbl>
#> 1 1            20        80  0.1   9         0
#> 2 1            20        80  0.13  6.69      0
#> 3 1            20        80  0.17  4.88      0
#> 4 1            20        80  0.2   4         0
#> 5 1            20        80  0.25  3         0
#> 6 1            20        80  0.33  2.03      1