Package: mcradds 1.1.1.9000

mcradds: Processing and Analyzing of Diagnostics Trials

Provides methods and functions to analyze the quantitative or qualitative performance for diagnostic assays, and outliers detection, reader precision and reference range are discussed. Most of the methods and algorithms refer to CLSI (Clinical & Laboratory Standards Institute) recommendations and NMPA (National Medical Products Administration) guidelines. In additional, relevant plots are constructed by 'ggplot2'.

Authors:Kai Gu [aut, cre, cph]

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mcradds.pdf |mcradds.html✨
mcradds/json (API)
NEWS

# Install 'mcradds' in R:
install.packages('mcradds', repos = c('https://kaigu1990.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/kaigu1990/mcradds/issues

Pkgdown site:https://kaigu1990.github.io

Datasets:
  • PDL1RP - PD-L1 Reader Precision Data
  • adsl_sub - CDISC ADSL Subsetting Data
  • calcium - Reference Interval Data
  • glucose - Inermediate Precision Data
  • ldlroc - Two-sampled Paired Test Data
  • nonparRanks - Nonparametric Rank Number of Reference Interval
  • platelet - Quantitative Measurement Data
  • qualData - Simulated Qualitative Data

On CRAN:

in-vitro-diagnosticivdmcr

4.00 score 1 stars 7 scripts 306 downloads 36 exports 93 dependencies

Last updated 6 months agofrom:097752819c. Checks:8 OK. Indexed: yes.

TargetResultLatest binary
Doc / VignettesOKFeb 02 2025
R-4.5-winOKFeb 02 2025
R-4.5-macOKFeb 02 2025
R-4.5-linuxOKFeb 02 2025
R-4.4-winOKFeb 02 2025
R-4.4-macOKFeb 02 2025
R-4.3-winOKFeb 02 2025
R-4.3-macOKFeb 02 2025

Exports:%>%anovaVCAaucTestautoplotblandAltmancalcBiascat_with_newlinedescfreqdescvardiagTabdixon_outlierESD_testesd.criticalgetAccuracygetCoefficientsgetOutlierh_differenceh_factorh_fmt_count_perch_fmt_esth_fmt_numh_fmt_rangeh_summarizemcregnonparRIpearsonTestprintSummaryrefIntervalrobustRIsize_ci_corrsize_ci_one_propsize_corrsize_one_propspearmanTesttukey_outlierVCAinference

Dependencies:askpassbackportsbase64encbitbit64bootcellrangercheckmateclassclicliprcolorspacecpp11crayoncurldata.tableDescToolsdigestdplyre1071Exactexpmfansifarverfastmapforcatsformattersgenericsggplot2gldgluegtablehavenhmshtmltoolshttrisobandjsonlitelabelinglatticelifecyclelme4lmommagrittrMASSMatrixmcrmgcvmimeminqamunsellmvtnormnlmenloptrnumDerivopensslpillarpkgconfigplyrprettyunitspROCprogressproxypurrrR6rbibutilsRColorBrewerRcppRcppArmadilloRcppEigenRdpackreadrreadxlreformulasrematchrlangrobslopesrootSolverstudioapiscalesstringistringrsystibbletidyrtidyselecttzdbutf8VCAvctrsviridisLitevroomwithr

Introduction to mcradds

Rendered frommcradds.Rmdusingknitr::rmarkdownon Feb 02 2025.

Last update: 2023-12-04
Started: 2023-09-22

Readme and manuals

Help Manual

Help pageTopics
'mcradds' Packagemcradds-package mcradds
CDISC ADSL Subsetting Dataadsl_sub
ANOVA-Type Estimation of Variance Components for Random ModelsanovaVCA
AUC Test for Paired Two-sample MeasurementsaucTest
Generate a 'ggplot' for Bland-Altman Plot and Regression Plotautoplot autoplot,BAsummary-method autoplot,MCResult-method
BAsummary ClassBAsummary BAsummary-class
Calculate Statistics for Bland-AltmanblandAltman
Systematical Bias Between Reference Method and Test MethodcalcBias
Reference Interval Datacalcium
Concatenate and Print with Newlinecat_with_newline
Descriptive Statistics ClassDesc Desc-class
Summarize Frequency Counts and Percentagesdescfreq
Summarize Descriptive Statisticsdescvar
Creates Contingency TablediagTab
Detect Dixon Outlierdixon_outlier
EDS Test for OutliersESD_test
Compute Critical Value for ESD Testesd.critical
Summary Method for 'MCTab' ObjectsgetAccuracy getAccuracy,MCTab-method
Get Regression CoefficientsgetCoefficients
Detect Outliers From 'BAsummary' ObjectgetOutlier getOutlier,BAsummary-method
Inermediate Precision Dataglucose
Compute Difference for Bland-Altmanh_difference
Factor Variable Per Levelsh_factor
Format count and percenth_fmt_count_perc
Format and Concatenate to Stringh_fmt_est
Format Numeric Datah_fmt_num
Format and Concatenate to Rangeh_fmt_range
Summarize Basic Statisticsh_summarize
Two-sampled Paired Test Dataldlroc
Comparison of Two Measurement Methods Using Regression Analysismcreg
MCTab ClassMCTab MCTab-class
Nonparametric Rank Number of Reference IntervalnonparRanks
Nonparametric Method in Calculation of Reference IntervalnonparRI
PD-L1 Reader Precision DataPDL1RP
Hypothesis Test for Pearson Correlation CoefficientpearsonTest
Quantitative Measurement Dataplatelet
Print Summary of a Regression AnalysisprintSummary
Simulated Qualitative DataqualData
Reference Interval ClassRefInt RefInt-class
Calculate Reference Interval and Corresponding Confidence IntervalrefInterval
Robust Method in Calculation of Reference IntervalrobustRI
SampleSize ClassSampleSize SampleSize-class
Show Method for Objectsshow show,BAsummary-method show,Desc-method show,MCTab-method show,RefInt-method show,SampleSize-method show,tpROC-method
Sample Size for Testing Confidence Interval of Pearson's correlationsize_ci_corr
Sample Size for Testing Confidence Interval of One Proportionsize_ci_one_prop
Sample Size for Testing Pearson's correlationsize_corr
Sample Size for Testing One Proportionsize_one_prop
Hypothesis Test for Spearman Correlation CoefficientspearmanTest
Test for Paired ROC ClasstpROC tpROC-class
Detect Tukey Outliertukey_outlier
Inferential Statistics for VCA-ResultsVCAinference