Extract workflow results as a plain data frame

Returns a fitted workflow's results as an ordinary data frame, so results can be filtered, joined, or written out without scraping printed output.

A workflow column is prepended so that tables from several analyses can be stacked and stay identifiable.

Usage

# S3 method for class 'contentvalid_workflow'
as.data.frame(
  x,
  row.names = NULL,
  optional = FALSE,
  component = c("results", "scale_summary"),
  include_interpretation = TRUE,
  ...
)

Arguments

x

A fitted contentvalid_workflow object.

row.names, optional

Present for compatibility with the generic.

component

Which component to return: "results" (the default, one row per unit of analysis) or "scale_summary".

include_interpretation

Keep the per-unit interpretation text. It is informative but long, so set FALSE for compact tables.

...

Ignored.

Value

A data frame.

Filtering is your decision, not the package's

There is deliberately no helper that returns "the items that passed." Selecting on status == "Supported" is a substantive decision that should appear in your own code where a reader can see it, and Review never means an item must be dropped. Keeping the filter explicit keeps that judgment visible in the analysis script and in the manuscript.

Examples

sorts <- read.csv(
  system.file("extdata", "sort_example.csv", package = "contentvalidR"),
  stringsAsFactors = FALSE
)
fit <- sort_validity(sorts)
head(as.data.frame(fit, include_interpretation = FALSE))
#>    workflow item target n_total  n n_missing n_target competitor n_other_max
#> 1 item-sort   A1      A      20 20         0       18       B; C           1
#> 2 item-sort   A2      A      20 20         0       15          B           3
#> 3 item-sort   B1      B      20 20         0       17          A           2
#> 4 item-sort   B2      B      20 20         0       13          A           5
#> 5 item-sort   C1      C      20 20         0       18       A; B           1
#> 6 item-sort   C2      C      20 20         0       14          B           4
#>    psa   psa_low  psa_high  csv      p_value critical_n_target passes_chance
#> 1 0.90 0.6989664 0.9721335 0.85 0.0002012253                15          TRUE
#> 2 0.75 0.5312991 0.8881383 0.60 0.0206947327                15          TRUE
#> 3 0.85 0.6395811 0.9476313 0.75 0.0012884140                15          TRUE
#> 4 0.65 0.4328543 0.8188082 0.40 0.1315879822                15         FALSE
#> 5 0.90 0.6989664 0.9721335 0.85 0.0002012253                15          TRUE
#> 6 0.70 0.4810272 0.8545228 0.50 0.0576591492                15         FALSE
#>   recommendation                                   issue    status
#> 1         Retain                               Supported Supported
#> 2         Retain                               Supported Supported
#> 3         Retain                               Supported Supported
#> 4         Review Target favored, exact criterion not met    Review
#> 5         Retain                               Supported Supported
#> 6         Review Target favored, exact criterion not met    Review
as.data.frame(fit, component = "scale_summary")
#>    workflow target n_items n_items_usable n_retain n_review mean_psa
#> 1 item-sort      A       2              2        2        0    0.825
#> 2 item-sort      B       2              2        1        1    0.750
#> 3 item-sort      C       2              2        1        1    0.800
#>   psa_strength mean_csv csv_strength orbiting_r
#> 1       Strong    0.725       Strong         NA
#> 2     Moderate    0.575     Moderate         NA
#> 3     Moderate    0.675       Strong         NA
#>                      benchmark_set benchmark_applicable overall_strength
#> 1 Overall (not correlation-normed)                 TRUE           Strong
#> 2 Overall (not correlation-normed)                 TRUE         Moderate
#> 3 Overall (not correlation-normed)                 TRUE         Moderate
#>                                                                                                                                       evidence
#> 1                                              The weaker of Psa and Csv falls in the Strong band of published scales (Colquitt et al., 2019).
#> 2 The weaker of Psa and Csv falls in the Moderate band of published scales (Colquitt et al., 2019); review the weaker items before finalizing.
#> 3 The weaker of Psa and Csv falls in the Moderate band of published scales (Colquitt et al., 2019); review the weaker items before finalizing.