The following is one of the best introductions to R programming that I've found online. It is part of a larger series of tutorials created by Jared Knowles called R Bootcamp. Jared's tutorials are a valuable resource for anyone try to learn to program in R. Below the presentation are links to the handouts and R Code that are used during the HTML5 presentation that is linked below. Enjoy!

Read MoreThis is a fantastic resource created by Dr. William Revelle for running confirmatory factor analysis (CFA) models and structural equation models (SEM) in R using the lavaan package. The tutorial walks through example models, includes example code, discusses multi-group analysis, and even references some advanced functions for producing path diagrams using the psych package in R.

Read More*Part 3 we used the lm() command to perform least squares regressions. In Part 4 we will look at more advanced aspects of regression models and see what R has to offer. One way of checking for non-linearity in your data is to fit a polynomial model and check whether the polynomial model fits the data better than a linear model. Or you may wish to fit a quadratic or higher model because you have reason to believe that the relationship between the variables is inherently polynomial in nature.*

*Let’s see how to fit a quadratic model in R...*