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Introduction to R

Darrin Rogers (not any kind of R expert guy) Department of Psychology & Anthropology University of Texas – Pan American 4/14/2011. Introduction to R. Installing R. Do this while I’m rambling on about R… http://cran.revolution-computing.com/ (CRAN mirror in San Antonio)

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Introduction to R

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  1. Darrin Rogers (not any kind of R expert guy) Department of Psychology & Anthropology University of Texas – Pan American 4/14/2011 Introduction to R

  2. Installing R Do this while I’m rambling on about R… • http://cran.revolution-computing.com/ • (CRAN mirror in San Antonio) • Installationfileis in [OS]  base • Install wizard; defaults are probably OK for now • If no admin rights, install to C:\R • Choose a working directory • Actually any number of them…. • Make a shortcut to Rgui.exe • Change target directory in shortcut properties

  3. Where did R come from? • S development started in 1976 (commercial) • John Chambers et al., Bell labs • 4 major revisions through 1990s • Mid- 990s: R (Ross Ihaka & Robert Gentleman) • 1997 – R Core Team – modify source code • CRAN • R-project.org • Users: 200,000 – 10,000,000+ … ? Hard to say.

  4. What is R? • Core: interpreted computer language • Developed principally for stats • Branching and looping • Modular programming using functions • Package: Base • Essential low-level functions • Other packages • Lots and lots • Severalincluded in “basicinstall” • About 3,000 availablethrough CRAN • FREE & open-source

  5. Basic R Resources • Comprehensive R Archive Network (CRAN) • cran.r-project.org • Package and Base downloads • Google • R-Help mailing list archives • Google • Websites made for R users • Google

  6. Installing Packages • Psych Install.packages(“psych”) • Load package library(psych) • Get help ?psych • Google “R-package psych” • Documentation (a bit arcane) • Google  easier-to-understand guides

  7. R basics • Use a text editor • I like notepad++ (“R aware”) • Notepad works OK • Case-sensitive! • Psych ≠ psych • Help ?something ??something RSiteSearch(“something”) • google

  8. Objects • Many kinds of objects • Strings • Lists • Matrices • Data frames • Functions • Many types (often created for packages) ls() # lists all objects in current workspace

  9. Assignment • = or <- assigns value/data to an object • Try this: x <- 5 x phrase <- “hello world” phrase x <- c(2, 3, 4, 5, 9, 10, 11, 12) # any list of numbers x

  10. hints • R usually ignores spaces • Strings belong in quotes • ‘string’ • “string” • Write your syntax in a file  copy&paste • Use lots of comments • # comments help you remember next year • One workspace per project • (or even one per analysis)

  11. Using functions • function(thingToBeFunctionated) mean(x) sd(x) hist(x) (x-mean(x))/sd(x)# z-scores Assign output of function to an object z <- (x-mean(x))/sd(x) z <- scale(x)

  12. Easy Regression • Example 1 (text file)

  13. Import Data from .csv Example 2 (text file, pun_dat.csv) • Get data into .csv • From Excel or SPSS  Save As • read.csv() • Puts data into data.frame object • (a specialized matrix) names(data) # I find uppercase names annoying names(data) <- casefold(names(data))

  14. data.frame objects: indexing • Specifying variables within the data.frame $ data$p_age • Specifying values within the variable  [] data.frame$variable[value] data$p_age[10] data.frame[row,col] data[10,5]

  15. Attaching objects (data frames) • attach() makes the data.frame “available” • Reference variables w/o naming the data.frame • Annoying properties • Can attach multiple copies/layers by accident • Changes are not permanent; just a copy • Must detach() then attach() for changes to stick • If no planned changes to data… attach(data)

  16. Some Things Are Easier in R • Histogram of number of sex offenders known hist(numoffsknown) • Histogram of transformed variable hist(log(numoffsknown))

  17. Some Things Are Easier in R • Histogram of accountability ratings (SO+NSO) hist(so_nso_acc, col=“#EE0000") • Histogram of undergrad accountability ratings hist(so_nso_acc[which(trt_pro==0)], col="#00EE00") • Histogram of therapist accountability ratings hist(so_nso_acc[which(trt_pro==1)], col="#0000EE85", add=TRUE)

  18. More Regression – GLM Example 3 (text file) • Outcome = number of offenders known • Predictors: • Participant age p_age • Treatment professional trt_pro • Political affiliation p_politaffil • Use “quasi-poisson” link function

  19. ANOVA Example 4 (text file) • 2x3 ANOVA • Dependent: so_nso_pun overall punishment rating • Factor 1: o_dev_level (child, adolescent, adult) • Factor 2: trt_pro (yes, no) • R quirk: must turn factors into “factors” • Basic: lm() and then anova() of the result • Shortcut: aov()

  20. Fun Graphs Example 5 • Scatterplots & correlograms Example 6: • Boxplot with extras

  21. Writing Functions • Becomes easier fairly quickly • Extremely useful! • This is what lots of people do instead of downloading packages Example 7 • My function: compute probability that at least two people in a group of size n will have the same birthday

  22. Other Stuff • Multiple imputation • Robust Regression, Loess Curves • Factor Analysis… OK? • Power analysis • ROC curves • Really cool and awesome graphs I don’t need • Lots of esoteric analyses I don’t understand

  23. Disadvantages & Annoyances • Yeah, I guess there’s a bit of a learning curve • Eventually you’ll need to start coding • Nothing really like SPSS data view • edit() is clunky & problematic • Some simple things are ridiculously complex • Beta values in regression • Specifying individual values in a dataset • Rememberingna.rm=TRUE formanyfunctions • Culture of R ≠ psychologyculture • Documentation is created by & for mathematicians and computer programmers • SEM packages… Not so great (yet)

  24. Some (of Many) Resources • CRAN network: • http://cran.revolution-computing.com/ • R-project • http://www.r-project.org/ • R-help mailing list (customer support… kinda) • https://stat.ethz.ch/mailman/listinfo/r-help • The R Personality Project (R for psychology) • http://www.personality-project.org/r/

  25. More Resources • Quick commands (there are lots of sites like this!) • http://www.personality-project.org/r/r.commands.html • Good intro (there are lots of these, too) • http://www.personality-project.org/r/book/AppendixA.pdf • Quick-R … Awesome resource • http://www.statmethods.net/index.html • Jonathan Barron’s R Help Page • http://finzi.psych.upenn.edu/ • Another good intro site • http://msenux.redwoods.edu/math/R/

  26. Moar Resources • ANOVA • http://www.statmethods.net/stats/anova.html • http://www.personality-project.org/r/r.anova.html • Graphs/Graphics • http://www.harding.edu/fmccown/R/#misc • http://addictedtor.free.fr/graphiques/ • http://www.stat.auckland.ac.nz/~paul/RGraphics/rgraphics.html • http://zoonek2.free.fr/UNIX/48_R/03.html

  27. Yet more • Robust Regression • http://www.ats.ucla.edu/stat/r/dae/rreg.htm • Writing Functions • http://fs6.depauw.edu:50080/~harvey/Chem%20351/PDF%20Files/Handouts/RDocs/Writing%20Functions%20Using%20R.pdf • GLMs (e.g., logistic, poisson) • http://data.princeton.edu/R/glms.html • http://www.stanford.edu/class/stats306a/RforGLM.pdf • http://www.jstatsoft.org/v08/i15/paper

  28. How to Get Help • From within R • RSiteSearch(“xxx”) • ?xxxx or help(“xxx”) • Google • “R-Help xxx” • “R package xxx” • “R how-to xxx” drogers1@utpa.edu

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