R language

Cover Page

Introduction, Installation and Basic Principles

Data frames

Types of data

Data visualization with graphs

A useful graphics package

Coloring the points by a grouping variable

Jittered points

Line graphs

Barplots

Barplots with Multiple Groups

Stacked barplots

Boxplots

Grouped boxplots

Notched boxplots

Violin plot

Combination graphs

Flipping the axes

Multiple variable plot

Regression line

Non-linear Smooth curve

Density plot

Plotting vertical and horizontal lines

Putting text on plot

Tile plot

Histogram

Histogram using ggplot2

Angled x-axis labels

Adding title and axis labels to plot of base R

Adding title and axis-labels to ggplots

Lineplot with points and confidence intervals

Prism Plot

Type of distributions

Test to assess distribution

Converting non-normal to normal distributions

Summarizing data

Stars plot

Tableplot

Creating a 3-D scatterplot

Mouse - rotatable 3D plots

Parametric versus non-parametric tests

Testing correlation

Graphical representation of correlation

Correlation matrix

Item Cluster Analysis

Omega estimates

Creating clusters from data

Score-based Structure Learning

Summary of data by group

Parallel Coordinate Plot

Linear Discriminant Analysis

Creating algorithm using classfication and trees

Rotatable 3d plots with principal component analysis

Comparing 2 groups: unpaired data

Graphical representation of 2 numeric groups

Effect size for comparison of 2 numeric groups

Graphical representation of paired data

Comparing many groups

Graphical representation of multiple numeric groups

Contingency tables

Graphical representation of contingency table

Effect size: Odds ratio

Multiple regression

Multiple regression for binary outcome

Multiple regression for ordinal outcome

Multiple regression for multiple categorical outcome (multinomial regression)

Regression diagnostics

Repeated measures ANOVA

Analysis of Pre-Post Treatment-Control studies

Graphic visualization of pre-post active-control data

Stepwise regression

Linear regression using package rms

Logistic and ordinal regression using rms package

Regression after Box-Cox transformation

RegBest of FactoMineR package

Most important predictors with bestglm package

Robust regression

Robust regression using robustbase package

Bayesian regression

MCMCregress of MCMCpack (Markov Chain Monte Carlo)

Ridge, Elastic net and Lasso regression

Partial least squares (pls) regression

Relative importance of predictors

Principal component analysis

Factor analysis

Multiple correpondence analysis

Dendrograms

Multidimensional Scaling

Andrews curves

Cluster analysis

Canonical correlation analysis

Survival analysis

Partial Least Squares Discriminant Analysis

Growth charts

Structural equation modelling

Meta-analysis

Bootstrap

Evaluating a new test: Sensitivity, specificity, ROC curve & other parameters

Nomograms

Creating predictive models

Bland Altman Plot

Author

Citations

Comments & Feedback