Generate RRS (Relative Rigor Score) table row for an applicant

Creates a data frame row containing the applicant's name, overall RRS score, and sector-specific scores with visualizations for Open Data, Open Materials, Preregistration, and Reproducible Code categories. For the overview report, multiple rows can be combined into a summary table.

Usage

get_RRS_tablerow(applicant, add_scores = FALSE)

Arguments

applicant: The applicant information, as returned by the preprocess function.
add_scores: Shall the scores for the sectors be added as columns? (This is needed for sorting in the overview report.)

Value

A data frame with one row containing:

applicant: Character string of the applicant's last name
Relative Rigor Score: HTML visualization of the overall RRS score as a circle
Open Data: HTML visualization combining waffle chart and ministack, or "N/A" if not applicable
Open Material: HTML visualization combining waffle chart and ministack, or "N/A" if not applicable
Preregistration: HTML visualization combining waffle chart and ministack, or "N/A" if not applicable
Reproducible Code/Reproducible Code & Verification: HTML visualization combining waffle chart and ministack, or "N/A" if not applicable

Details

The function extracts sector-specific scores from the applicant's RRS data and creates HTML visualizations for each category. The visualizations consist of:

A circular visualization for the overall RRS score
Waffle charts showing the distribution of practices
Ministack visualizations showing the relative scores

The function handles missing data gracefully by returning "N/A" for categories without scores.

Examples

if (FALSE) { # \dontrun{
# Example applicant structure
applicant <- list(
  meta = list(FullName = "John Doe"),
  RRS = list(
    overall_score = 0.75,
    sector_scores = data.frame(
      category = c("Open Data", "Open Materials", "Preregistration", "Reproducible Code"),
      rel_score = c(0.8, 0.7, 0.6, 0.9),
      max_points = c(10, 10, 10, 10)
    )
  ),
  OS_pie = list(
    OpenData = c(Yes = 5, Aggregate = 2, Partial = 1, No = 1, notApplicable = 1),
    OpenMaterial = c(Yes = 3, Partial = 2, No = 3, notApplicable = 2),
    Prereg = c("Registered Report" = 2, Preregistration = 3,
               "Not preregistered" = 3, "Not Applicable" = 2),
    OpenCode = c(Yes = 6, Partial = 2, No = 1, notApplicable = 1)
  )
)

result <- get_RRS_tablerow(applicant)
} # }