# Lesson Archives

1. ## Inter-Rater Reliability Analyses: Quick R Codes

This article describes how to compute the different inter-rater agreement measures using the irr packages.

3. ## Intraclass Correlation Coefficient in R

This chapter explains the basics of the intra-class correlation coefficient (ICC), which can be used to measure the agreement between multiple raters rating in ordinal or continuous scales. We also show how to compute and interpret the ICC values using the R software.
4. ## Fleiss' Kappa in R: For Multiple Categorical Variables

This chapter explains the basics and the formula of the Fleiss kappa, which can be used to measure the agreement between multiple raters rating in categorical scales (either nominal or ordinal). We also show how to compute and interpret the kappa values using the R software.
5. ## Weighted Kappa in R: For Two Ordinal Variables

This chapter explains the basics and the formula of the weighted kappa, which is appropriate to measure the agreement between two raters rating in ordinal scales. We also show how to compute and interpret the kappa values using the R software.
6. ## Cohen's Kappa in R: For Two Categorical Variables

This chapter describes the basics and the formula of the Cohen’s kappa for two and more variables. Additionally, we show how to compute and interpret the kappa coefficient in R.
7. ## Introduction to R for Inter-Rater Reliability Analyses

This chapter provides a quick introduction to R and a brief description of how to work with categorical data in R. You will learn how to create contingency tables.
8. ## Combine Multiple GGPlots into a Figure

This article describes how to combine multiple ggplots into a figure. You will learn how to use: 1) ggplot2 facet functions for creating multiple panel figures that share the same axes; 2) ggarrange() functiong [ggpubr package] for combining independent ggplots.
9. ## GGPlot ECDF

ECDF (or Empirical cumulative distribution function) provides an alternative visualization of distribution. It reports for any given number the percent of individuals that are below that threshold. This article describes how to create an ECDF in R using the function stat_ecdf() in ggplot2 package.
10. ## GGPLOT QQ Plot

A Quantile-quantile plot (or QQPlot) is used to check whether a given data follows normal distribution. The data is assumed to be normally distributed when the points approximately follow the 45-degree reference (diagonal) line. This article describes how to create a qqplot in R using the ggplot2 package.