contentvalidR 0.5.0

Fifth public release. v0.5.0 adds a workflow for Delphi studies, where the same
expert panel rates items over successive rounds. It reports consensus and
stability as separate questions, and every published stability method is
available with its limits printed. The handoff to empirical validation now
carries each statistic's interval, so a downstream analysis can see how much
panel evidence stands behind a number.

The package continues to declare Imports: stats only.

No default changes. Existing calls return the same values as in 0.4.0.
content_handoff() objects gain four interval columns in item_statistics
and a panel_statistics table, within schema version 1.

New function: delphi_validity(). New article: vignette("delphi-rounds").

This release is published on GitHub and R-universe. 0.4.0 is still in CRAN's
review queue, and CRAN policy asks that no further version be submitted while
one is pending, so 0.5.0 will be submitted to CRAN later as an update.

Delphi consensus and stability

• New workflow delphi_validity() for an expert panel rated over successive
  Delphi rounds (#20).
  It reports two questions separately. Consensus: whether enough experts
  agree now. Stability: whether experts are still changing their ratings.

  • Consensus is the share of experts rating an item at or above
    agree_cut, which on a relevance scale is the I-CVI. It is judged
    against a consensus_threshold fixed before the study. There is
    deliberately no default: without a threshold, results are descriptive
    (Diamond et al., 2014).

  • Stability always reports the share of experts who kept their rating.
    Beside it goes one statistic:

    • the default, weighted kappa between rounds (Holey et al., 2007), read
      as a trend. Quadratic weights, the default, make it the intraclass
      correlation of the two rounds (Fleiss & Cohen, 1973); linear weights
      are available (Cohen, 1968);
    • Chaffin & Talley's (1980) lambda;
    • Chaffin & Talley's individual chi-square;
    • Dajani, Sincoff & Talley's (1979) group chi-square;
    • Scheibe, Skutsch & Schofer's (1975) 15% net-change rule.

    Each alternative's limits are printed. The two chi-square tests read in
    opposite directions, and the printout says which is which.

  • No verbal kappa labels. Landis & Koch (1977) call their divisions
    arbitrary, and kappa falls as a panel converges. When a round is
    unanimous, kappa is 0 however many experts kept their rating; the output
    flags this and points to the share unchanged.

  • A bootstrap interval for kappa, resampling experts, marked as this
    package's extension.

  • Round-by-round relevance evidence. Each round is also fitted with
    expert_validity(), so compare_rounds() can read the whole process.

• New vignette, vignette("delphi-rounds"), walks through a three-round
  panel for a graduate reader. Its worked example covers:
  • a statement set aside after reaching consensus;
  • an expert leaving the panel;
  • consensus against a statement;
  • a stable split;
  • a panel converging to unanimity, where kappa drops to 0;
  • experts swapping ratings while the overall distribution stays still,
    which only individual stability detects.
• contentvalid_glossary("delphi") defines the new columns.
• Every published value used to design the workflow is a test: Cohen's
  (1968) Table 1, Fleiss & Cohen's equivalence, and the worked examples of
  Dajani et al. and Chaffin & Talley.

Interval bounds in the handoff

• content_handoff() now carries each statistic's interval
  (#33), so a reader can
  tell a unanimous four-judge panel from a unanimous twenty-judge one. A
  unanimous I-CVI from four experts has a Wilson 95% lower limit near 0.51.
  • item_statistics gains lower, upper, interval_method, and
    interval_level. They hold the Penfield-Giacobbi score interval for
    Aiken's V, and whichever proportion_ci method was chosen for I-CVI and
    Psa.
  • A new panel_statistics table carries the panel agreement coefficient
    and its bootstrap interval, which are not per item.
  • NA in all four columns means the statistic has no interval, never
    missing data.
• These additions stay within schema version 1, as agreed with nomologR on
  nomologR#46.
  • Existing fields keep their names, types, meaning, and column positions.
  • A reader should check that the new columns are present before using
    them.
• The handoff reports intervals only. It does not turn them into priors or
  weights.