Datasets and Code

Like many psychology students of recent times I was brought up in point-and-click style, patting myself on the back whenever output magically appeared and pretending I knew what I was talking about with regard to such legerdemain. What I came to learn was that simply getting output is something wholly different than doing statistical analysis, and that to do a good analysis requires getting one's hands dirty.

However, I also don't think it's necessary to become a computer programmer outright (or at least shouldn't be). One can take what is necessary and use it in an applied fashion, doing much better analyses and more efficient ones. As such code is provided for lab content below so that you can spend more time on understanding the analysis, with some additional stuff for R, my preferred stat program. The SAS will not be great as it is my preference to not use it if I can help it. I find I like it as a program better than SPSS in terms of what it can do, but just about everything regarding it is 'ugly' in appearance. Neither syntax is as flexible as R, and almost always requires much more code to do the same thing. Also, if you come across a more efficient way to do something definitely let me know and I'll put it up here. For lab specific code click here.

Code relevant to labs
Purpose	R	SPSS	SAS
Entering Data	X	X	X
Importing Data	X	X	X
Manipulating Data	X	X
Frequencies	X	X	X
Central Tendency and Variability	X	X	X
Summary Statistics	X	X	X
t-tests	X	X
Correlation	X	X	X
Simple Regression	X	X
Power and Effect Size	X	N/A
Datasets Most datasets used in class and lab demonstration may now be accessed here. Text files automatically load into the browser, just access and save when you see it on your screen. For SPSS files, download when the dialog box presents itself to. Note that by default Rcmdr imports the factor labels (i.e. the words rather than the numbers if there is a choice). If you prefer them or need them to stay numeric, uncheck that box that says 'convert value labels to factor levels' during the import process. Class dataset SPSS portable form Howell datasets. Karl Wuensch's datasets.
Useful R packages/functions General Pdf for installing R at home Quick R: an R website for SAS/SPSS/Stata Users R wiki R web interface and notes Using R in Psychological Research ANOVA and Regression in R (book) R graphics R colors R for SAS and SPSS Users Comparing those three packages Functions General Cran Task Views Wilcox, Workshop Fox, Robust appendix Basics t.test cor aov Regression General regression related functions Robust regression functions Bootstrapping boot bootstrap simpleboot Packages BMA: Bayesian model averaging Boot, simpleboot: basic bootstrap Design: useful functions for anova/regression, validation Hmisc: general purpose lme4 and nlme: mixed effects/multilevel modeling ltm: Item response theory MASS: evolved from Venerable and Ripley's Modern Applied Statistical Analysis MBESS: Behavioral Sciences specific, tons of effect size goodies Mike's Miscellaneous Multtest: multiple comparisons in ANOVA prettyR: make descriptive output 'pretty' Psy: psychometric stuff Psych: includes functions for personality and psychological research QuantPsyc: for testing moderation and mediation Quantreg: quantile regression R-commander: menu system Rcmdr.HH Relaimpo: measures relative importance of variables in multiple regression in a meaningful way Robust library that makes it easy, notes Robustbase: more robust regression sem: structural equation modeling Wilcox library (a host of robust functionality) Rallfun-v8 For Mike Miscellaneous and Wilcox libraries, right click and save them in your main R folder, and whenever you want to use the functions within, from the menu File/Source R code, then go find your file. Or at the command line source("Rallfunv1-v8") Where the quotes have the address of the file location. To see what's in them just open them up like any other script. See the Wilcox link for more info. With the Mike misc, Macs may have an issue sourcing the file, but if you just cut and paste the functions (just click the link rather than save) at the console that will work until I can figure out the issue. Help file for projects General psych/social science-related stuff in R Psychometrics: IRT, SEM etc. Social Science: general Multivariate Robust
Some examples of code I find useful: Cohen's d, R², Intervals for them Plotting Cohen's d False Discovery Rate Whizbang intervals Robust correlation and simple regression Bootstrap t-test (requires Wilcox libraries above) Robust regression (general) Simple Mediation Testing multivariate normality All subsets regression: note that it is better accomplished in the R-commander menu system if you install the Rcmdr.HH library (see above). You even get a nice graphic. Validation of a linear model Path analysis of lecture notes example Creating a dataset Plotting interactions in regression
Other Simple effects SPSS syntax R, S-Plus, SAS and SPSS scripts for CIs for effect sizes (Smithson)

Code relevant to labs

Datasets

Useful R packages/functions

Some examples of code I find useful: