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GarrettRank provides functions for conducting Garrett ranking analysis. The package is designed to calculate Garrett scores from respondent-level ranking data and provide summarized ranking results in a convenient format.
The package also provides functions for generating tables, summaries,
visualizations, and Kendall’s coefficient of concordance for assessing
agreement among respondents. Visualizations are built using
ggplot2 and pheatmap.
The package can be installed using:
install.packages("GarrettRank")Then load the package:
library(GarrettRank)The main functions provided by GarrettRank are:
garrett_rank() — performs Garrett ranking
analysis.garrett_table() — produces the standard Garrett
ranking/percent position conversion table used in the scoring
calculation.kendall_w() — calculates Kendall’s coefficient of
concordance.The package also provides S3 methods for:
summary()plot()The package includes an example dataset called
garrett_example.
The dataset contains:
C1 to C22)The dataset can be loaded using:
data("garrett_example")
head(garrett_example)library(GarrettRank)
data("garrett_example")
# Perform Garrett ranking
result <- garrett_rank(garrett_example, respondent = "Respondent")
# View the result
result
# Summary
summary(result)
# Plot the results
plot(result)data accepts a data.frame, matrix, CSV file path, or
Excel file path. Each row should represent one respondent and each
column one factor/constraint, with every respondent assigning each rank
from 1 to the number of factors exactly once. respondent
specifies the column name or position containing respondent IDs, so it
can be excluded before analysis.
plot() supports several type options,
covering both item-level ranking summaries and respondent-level
agreement patterns:
type |
Description |
|---|---|
| (default) | Default summary plot of Garrett scores by item. |
"bar" |
Bar chart of Garrett scores by item. |
"lollipop" |
Lollipop chart of Garrett scores by item. |
"dot" |
Dot plot of Garrett scores by item. |
"line" |
Line plot of Garrett scores by item. |
"heatmap" |
Ranks × item score heatmap. |
"cluster" |
Hierarchical clustering of respondents by ranking pattern. |
"contribution" |
Contribution of each item to the overall Garrett score. |
Additional arguments for type = "cluster":
k — number of clusters to highlight (e.g.,
k = 3).scale — scaling applied before clustering (e.g.,
scale = "row").show_numbers — whether to display values on the cluster
heatmap.plot(result, type = "bar")
plot(result, type = "lollipop")
plot(result, type = "dot")
plot(result, type = "line")
plot(result, type = "heatmap")
plot(result, type = "cluster")
plot(result, type = "cluster", k = 3)
plot(result, type = "cluster", scale = "row", show_numbers = TRUE)
plot(result, type = "contribution")Kendall’s coefficient of concordance can be calculated using:
kendall_result <- kendall_w(garrett_example, respondent = "Respondent")
kendall_result
summary(kendall_result)If you use GarrettRank in your research, please cite the package as:
Varghese, B. B., et al. GarrettRank: Garrett Ranking Analysis in R.
A formal citation will be added once the package is published. Once available, it can be retrieved with:
citation("GarrettRank")This package is licensed under the GPL-3 license.
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.