mrmcbinary

Multi-Reader Multi-Case Analysis of Binary Diagnostic Tests

https://github.com/seungjae2525/mrmcbinary

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Keywords

binary-data diagnostic-accuracy mrmc
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Multi-Reader Multi-Case Analysis of Binary Diagnostic Tests

Basic Info
  • Host: GitHub
  • Owner: seungjae2525
  • License: other
  • Language: R
  • Default Branch: master
  • Homepage:
  • Size: 195 KB
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binary-data diagnostic-accuracy mrmc
Created about 1 year ago · Last pushed about 1 year ago
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README.md

MRMCbinary

minimal R version CRAN status metacran downloads Project Status Lifecycle: stable R-CMD-check <!-- badges: end -->

Multi-Reader Multi-Case Analysis of Binary Diagnostic Tests

Description

This is the source code for the MRMCbinary package in R. MRMCbinary is a package aimed at comparing the performance of diagnostic tests (i.e., sensitivity and specificity) for a binary outcome in multi-reader multi-case (MRMC) study.

Reference

Lee, S., Jang, S., and Lee, W. Evaluating Diagnostic Accuracy of Binary Medical Tests in Multi-reader Multi-case Study.

Installation

The latest release version from CRAN:

r install.packages("MRMCbinary") library(MRMCbinary)

Current GitHub release:

Installation using R package devtools:

r if (!require("devtools")) { install.packages("devtools") } # if devtools not already installed devtools::install_github("seungjae2525/MRMCbinary") library(MRMCbinary)

Example

This is a basic example which shows you how to use MRMCbinary package:

``` r

Load MRMCbinary package

library(MRMCbinary)

Load example data

data(VanDyke)

Return the first parts of an object

head(VanDyke)

Extract unique modalities

unique(VanDyke$treatment)

Extract Unique readers

unique(VanDyke$reader)

Create binary test results (Y_ijk)

VanDyke$Y <- as.numeric(VanDyke$rating >= 3)

Example usage of MRMCbinary function:

When comparing the sensitivities and specificities between modalities

modalityresult <- MRMCbinary(data = VanDyke, Modality = treatment, Reader = reader, Case = case, D = truth, Y = Y, measure = "All", effect = "Modality", interaction = NULL, reference.Modality = "1", reference.Reader = NULL) print(modalityresult) summary(modality_result, digits = 3)

When comparing the sensitivities and specificities between readers

readerresult <- MRMCbinary(data = VanDyke, Modality = treatment, Reader = reader, Case = case, D = truth, Y = Y, measure = "All", effect = "Reader", interaction = NULL, reference.Modality = NULL, reference.Reader = "1") print(readerresult) summary(reader_result, digits = 3)

When comparing the sensitivities and specificities between modalities and between readers together

not considering interaction between modalities and readers

bothresultwoint <- MRMCbinary(data = VanDyke, Modality = treatment, Reader = reader, Case = case, D = truth, Y = Y, measure = "All", effect = "Both", interaction = FALSE, reference.Modality = "1", reference.Reader = "1") print(bothresultwoint) summary(bothresultwo_int, digits = 3)

When comparing the sensitivities and specificities between modalities and between readers together

considering interaction between modalities and readers

bothresultwithint <- MRMCbinary(data = VanDyke, Modality = treatment, Reader = reader, Case = case, D = truth, Y = Y, measure = "All", effect = "Both", interaction = TRUE, reference.Modality = "1", reference.Reader = "1") print(bothresultwithint) summary(bothresultwith_int, digits = 3) ```

Bug Reports:

You can also report bugs on GitHub under Issues.

Owner

  • Name: Seungjae Lee
  • Login: seungjae2525
  • Kind: user
  • Location: Korea
  • Company: Seoul national university

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  • Total packages: 1
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  • Total dependent repositories: 0
  • Total versions: 2
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cran.r-project.org: MRMCbinary

Multi-Reader Multi-Case Analysis of Binary Diagnostic Tests

  • Versions: 2
  • Dependent Packages: 0
  • Dependent Repositories: 0
  • Downloads: 232 Last month
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Dependent packages count: 27.3%
Dependent repos count: 33.6%
Average: 49.2%
Downloads: 86.7%
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Last synced: 6 months ago