Using R in 12 simple steps for personality research
(These steps are not meant to limit what can be done with R, but merely to describe how to do the analysis for the most basic of research projects and to give a first experience with R).
Install R on your computer or go to a machine that has it.
Download the psych package as well as other recommended packages from CRAN using
the install.packages function, or using the package installer in the GUI. To get packages recommended for a particular research field, use the ctv package to install a particular task view. Note, these first two steps need to be done only once!
Activate the psych package or other desired packages using e.g., library(psych). This needs to be done every time you start R. Or, it is possible to modify the startup parameters for R so that certain libraries are loaded automatically.
Enter your data using a text editor and save as a text file (perhaps comma delimited if using a spreadsheet program such as Excel or OpenOffice)
Read the data file or copy and paste from the clipboard (using, e.g., read.clipboard).
Find basic descriptive statistics (e.g., means, standard deviations, minimum and maxima)
using describe.
Prepare a simple descriptive graph (e.g, a box plot) of your variables.
Find the correlation matrix to give an overview of relationships (if the number is not
too great, a scatter plot matrix or SPLOM plot is very useful, this can be done with
pairs.panels.
If you have an experimental variable, do the appropriate multiple regression using stan-
dardized or at least zero centered scores.
If you want to do a factor analysis or principal components analysis, use the factanal or
fa and principal function
To score items and create a scale and find various reliability estimates, use score.items and perhaps omega.
Graph the results.
Rafa Llopis on 29 Apr 13Esta web afirma que la mejor ventaja del lenguaje R es que es una comunidad abierta y que mejora constantemente.
