Processing and Analyzing of Diagnostics Trials
ANOVA-Type Estimation of Variance Components for Random Models
AUC Test for Paired Two-sample Measurements
Generate a ggplot for Bland-Altman Plot and Regression Plot
BAsummary Class
Calculate Statistics for Bland-Altman
Systematical Bias Between Reference Method and Test Method
Concatenate and Print with Newline
Descriptive Statistics Class
Summarize Frequency Counts and Percentages
Summarize Descriptive Statistics
Creates Contingency Table
Detect Dixon Outlier
EDS Test for Outliers
Compute Critical Value for ESD Test
Summary Method for MCTab Objects
Get Regression Coefficients
Detect Outliers From BAsummary Object
Compute Difference for Bland-Altman
Factor Variable Per Levels
Format count and percent
Format and Concatenate to String
Format Numeric Data
Format and Concatenate to Range
Summarize Basic Statistics
mcradds Package
Comparison of Two Measurement Methods Using Regression Analysis
MCTab Class
Nonparametric Method in Calculation of Reference Interval
Hypothesis Test for Pearson Correlation Coefficient
Pipe operator
Print Summary of a Regression Analysis
Reference Interval Class
Calculate Reference Interval and Corresponding Confidence Interval
Robust Method in Calculation of Reference Interval
SampleSize Class
Show Method for Objects
Sample Size for Testing Confidence Interval of Pearson's correlation
Sample Size for Testing Confidence Interval of One Proportion
Sample Size for Testing Pearson's correlation
Sample Size for Testing One Proportion
Hypothesis Test for Spearman Correlation Coefficient
Test for Paired ROC Class
Detect Tukey Outlier
Inferential Statistics for VCA-Results
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'.
Useful links