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qapproach

qapproach implements a workflow to support consensus building based on Q method. It prepares participant-by-statement rankings, identifies group perspectives, computes consensus priority scores (cp-scores), validates results by bootstrap resampling, and creates figures.

Installation

# install.packages("qapproach") # after CRAN publication
# remotes::install_github("jgeschke/qapproach")

Basic workflow

library(qapproach)

raw <- read.csv2("test_data/TCA_strategies.csv")
rankings <- prepare_rankings(raw)
consensusal_priorities <- qapproach(rankings)
consensusal_priorities[["cp-scores"]]

cp-scores use a fixed standard-normal cumulative-probability scale. A value of 0.5 represents neutral prioritization across all group perspectives; higher and lower values represent relatively higher and lower priority. Cross-analysis comparisons require the same statements and meanings, ranking distribution, instructions, data preparation, and analytical settings.

For specialist inspection, the barplot can optionally overlay the weighted z-scores after rescaling them to the observed cp-score range:

plot_barplot(
  consensusal_priorities,
  show_normalized_weighted_z = TRUE,
  normalized_line_color = "black",
  normalized_line_width = 1.5
)

See vignette("qapproach") for analysis, validation, and visualization examples.

These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.
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