Package {catekappa}

catekappa: Design and Analysis of Categorical Agreement Tests Based on Kappa Statistics

Description

CATEKAPPA (Categorical Agreement Test Evaluation) provides a Shiny interactive application and supporting functions for the design and analysis of categorical agreement tests.

Details

This package wraps the core functionality of the irr and kappaSize packages:

• Design stage: Use calc_sample_size_kappa to calculate sample size, supporting 2–5 categories and 2+ raters.

• Analysis stage: Use analyze_kappa to compute Cohen's, Fleiss', and Light's Kappa statistics.

• Interactive app: Use run_cate_app to launch the Shiny interface.

Author(s)

Gai Zheng z2118778229@163.com Xincheng Li lxc409014@qq.com Yingjie Jiangwang 2312055564@qq.com Panwei Zhao 1581729526@qq.com

See Also

run_cate_app, calc_sample_size_kappa, analyze_kappa

Analyze Agreement Using Kappa Statistics

Description

Analyze consistency between raters using Cohen's, Fleiss', or Light's Kappa. Wraps functions from the irr package.

Usage

analyze_kappa(data, type = "cohen", detail = FALSE)

Arguments

Value

A list with kappa results, interpretation, and data summary.

Examples

data <- data.frame(
  Rater1 = c("Yes", "No", "Yes", "Yes", "No"),
  Rater2 = c("Yes", "No", "Yes", "No", "No")
)
analyze_kappa(data, type = "cohen")

Calculate Sample Size for Kappa Statistic

Description

Calculate required sample size for consistency tests. Directly wraps kappaSize::PowerBinary / Power3Cats / Power4Cats / Power5Cats.

Usage

calc_sample_size_kappa(
  kappa0 = 0.4,
  kappa1 = 0.6,
  props = c(0.5, 0.5),
  alpha = 0.05,
  power = 0.8,
  raters = 2
)

Arguments

Value

A list with sample size n and parameters.

Examples

calc_sample_size_kappa(kappa0 = 0.4, kappa1 = 0.6, props = c(0.5, 0.5))
calc_sample_size_kappa(kappa0 = 0.4, kappa1 = 0.6,
                       props = c(0.6, 0.3, 0.1), raters = 3)

Check Kappa Data Validity

Description

Internal function to validate input data for kappa analysis.

Usage

check_kappa_data(data, type = "cohen")

Arguments

Value

Logical indicating validity.

Interpret Kappa Value

Description

Interpret the strength of agreement based on Landis and Koch criteria.

Usage

interpret_kappa(kappa)

Arguments

Value

A named list with level, description, and color code.

Examples

interpret_kappa(0.3)
interpret_kappa(0.75)

Fixed N Analysis for Kappa Statistic

Description

Given a fixed sample size, estimate the lower confidence bound. Wraps kappaSize::FixedNBinary / FixedN3Cats / FixedN4Cats / FixedN5Cats.

Usage

kappa_fixed_n(n, kappa0 = 0.4, props = c(0.5, 0.5), alpha = 0.05, raters = 2)

Arguments

Value

List with kappaSize raw result and parameters.

Print Method for cate_analysis Objects

Description

Print Method for cate_analysis Objects

Usage

## S3 method for class 'cate_analysis'
print(x, ...)

Arguments

Print Method for cate_design Objects

Description

Print Method for cate_design Objects

Usage

## S3 method for class 'cate_design'
print(x, ...)

Arguments

Print Method for cate_fixed_n Objects

Description

Print Method for cate_fixed_n Objects

Usage

## S3 method for class 'cate_fixed_n'
print(x, ...)

Arguments

Run CATE Shiny Application

Description

Launch the Shiny application for design and analysis of consistency tests based on Kappa statistic with categorical responses.

Usage

run_cate_app(
  port = getOption("shiny.port"),
  launch.browser = getOption("shiny.launch.browser", interactive()),
  host = getOption("shiny.host", "127.0.0.1")
)

Arguments

Value

A Shiny application object (invisible).

Examples

if(interactive()){
run_cate_app()
}

Summary Method for cate_analysis Objects

Description

Summary Method for cate_analysis Objects

Usage

## S3 method for class 'cate_analysis'
summary(object, ...)

Arguments