An Introduction to the Use of R for Clinical Research
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1 An Introduction to the Use of R for Clinical Research Dimitris Rizopoulos Department of Biostatistics, Erasmus Medical Center [email protected] PSDM Event: Open Source Software in Clinical Research June 19th, 2012
2 Outline What is R and how to obtain in it Features of R Using R R and clinical research PSDM Event: Open Source Software in Clinical Research June 19th, /28
3 What is R? R is a free software environment for statistical computing and graphics. it was initiated in 1992 by Ross Ihaka and Robert Gentleman at University of Auckland, New Zealand in 1997 the R Core Team was established with renowned members of the statistical computing community nowadays, the R Core Team has grown and consists of about 20 members, experts in computing Free Software the source code is available users are allowed to modify and redistribute the code PSDM Event: Open Source Software in Clinical Research June 19th, /28
4 How to Install R? Download R from the CRAN web site choose your platform, e.g., Windows, Linux e.g., for Windows: Windows base Download R for Windows Install... Download R packages from the CRAN web site within R Packages Install package(s)... make your choice(s) load the package using library() (note: install does not mean load) PSDM Event: Open Source Software in Clinical Research June 19th, /28
5 Features of R Why R because is free it compiles and runs on a wide variety of UNIX platforms as well as Windows and MacOS R has extensive and powerful graphics & data manipulation capabilities it can easily interface with low-level programming languages, e.g., C/C++ or Fortran it can be easily extended via R packages PSDM Event: Open Source Software in Clinical Research June 19th, /28
6 Features of R (cont d) Disadvantages of R steep learning curve (some might say) output is not so nice looking (but there are some alternatives) * Sweave, odfweave exporting output is more difficult cannot easily handle very very big data sets (depends on the installed RAM) * use 64bit OSs a lot of things are available but it is sometimes hard to find your way the quality of the available packages is greatly varying PSDM Event: Open Source Software in Clinical Research June 19th, /28
7 Examples using R R is a command-based functional language write and execute commands use and define functions You may write the commands in the R console (Windows) or in a shell (Linux) Strongly advisable to use a suitable text editor Some available options: Tinn-R (for Windows; Rstudio (all major platforms; for more check rgui/projects/editors.html PSDM Event: Open Source Software in Clinical Research June 19th, /28
8 Examples using R (cont d) R has very flexible and compact syntax Example: Calculate the coefficient of variation (sample std. dev. / sample mean), for blood pressure separately for males and females, in the age groups (20, 40) and (40, 60), and conditionally of being obese (BMI > 30) or not with(bpdata, tapply(bp, list(cut(age, c(20, 40, 60)), sex, weight / height^2 > 30), function (x) sd(x)/mean(x)) PSDM Event: Open Source Software in Clinical Research June 19th, /28
9 Examples using R (cont d) Example: Fit a linear model for blood pressure levels taking as explanatory variables the linear and quadratic effects of age the main effect of gender and their interaction fm <- lm(bp ~ poly(age, 2) * sex, data = BPdata) summary(fm) # parameter estimates, standard errors, etc. plot(fm) # all basic residuals plots fitted(fm) # extract fitted values predict(fm, newdata) # make predictions for new patients PSDM Event: Open Source Software in Clinical Research June 19th, /28
10 Examples using R (cont d) Plotting Predicted values with 95% CIs per operation type xyplot(pred + low + upp ~ time TypeOp, data = Preds, type = "l", col = "black", lty = c(1,2,2), ylab = "Aortic Gradient (mmhg)", xlab = "Time (years)") PSDM Event: Open Source Software in Clinical Research June 19th, /28
11 Examples using R (cont d) Subcoronary Implantation Root Replacement Aortic Gradient (mmhg) Time (years) PSDM Event: Open Source Software in Clinical Research June 19th, /28
12 Reporting Results in R : The Standard Communicating the results of a statistical analysis perform the analysis using your preferred statistical software results from this analysis constitute the basis for a statistical report Usually, this is a two-stage procedure, first do the analysis, and then write the report Statistician s hope: I won t have to change the analysis after I have finalized the report unfortunately, this is seldom the case PSDM Event: Open Source Software in Clinical Research June 19th, /28
13 Reporting Results in R : An Alternative Embed the analysis into the report end up with only the report and data files Advantages reproducible reports dynamic reports Example: The client asks you to redo the whole analysis excluding some patients you just subset your original data and the report gets automatically updated!! PSDM Event: Open Source Software in Clinical Research June 19th, /28
14 Dynamic Reports with Sweave What is Sweave Sweave is a tool that allows to embed the output of R code in L A TEX documents How it works your report file will contain both documentation parts (written in L A TEX) and code parts (written in R) the code is evaluated in R the results as plain output or tables and/or figures are embedded into a final.tex file you can then run pdflatex or latex to produce a pdf of your report PSDM Event: Open Source Software in Clinical Research June 19th, /28
15 Dynamic Reports with Sweave (cont d) Requirements: if you know how to use R and L A TEX * no need to learn something new * Sweave ships directly with R * it is relatively straightforward to start using it if you do not know L A TEX * alternative: odfweave (open document format) PSDM Event: Open Source Software in Clinical Research June 19th, /28
16 Dynamic Reports with Sweave (cont d) Assuming basic R and L A TEX knowledge How does it work write your L A TEXfile as usual, but with extension.rnw instead of.tex e.g., myfile.rnw the file will also contain R code segments suitably separated from L A TEX from R execute Sweave("...\myfile.Rnw") this will create myfile.tex run L A TEX to obtain your report PSDM Event: Open Source Software in Clinical Research June 19th, /28
17 Dynamic Reports with Sweave (cont d) How do we combine the R and L A TEX source code using the Noweb syntax we separate between different segments (chunks) of source code, i.e., * << options >>= denotes the start of an R code chunk denotes the start of a documentation L A TEX chunk Basic options for code chunks label: an optional name for the chunk useful for locating errors echo: if TRUE, the commands are included in the document fig: if TRUE, it includes the plot created in the code PSDM Event: Open Source Software in Clinical Research June 19th, /28
18 Dynamic Reports with Sweave (cont d) Basic options for code chunks eval: if TRUE, the R code is evaluated results: * if hide, all output is completely suppressed * if tex, the output is taken to be already proper L A TEX markup and included as is * if verbatim, the output of R commands is included in a verbatim-like R output environment... (check?rweavelatex) PSDM Event: Open Source Software in Clinical Research June 19th, /28
19 Dynamic Reports with Sweave (cont d) More info/material for Sweave available online: many more Google it PSDM Event: Open Source Software in Clinical Research June 19th, /28
20 Getting Help in R Within R help.search("topic") or??"topic" (depends on the installed packages) RSiteSearch("topic") (requires internet connection) help() or? invoke the on-line help file for the specified function checking the FAQ On the internet R-help ( mailing list) R-seek ( Google-like searched engine) R-wiki ( PSDM Event: Open Source Software in Clinical Research June 19th, /28
21 Getting Help in R (cont d) On the internet CRAN Task Views ( categorization of packages) Crantastic ( categorization of packages + reviews) Equalis ( R forum) R4stats ( examples of basic R programs PSDM Event: Open Source Software in Clinical Research June 19th, /28
22 Getting Help in R (cont d) Intro with applications in statistics Dalgaard, P. (2008) Introductory Statistics with R, 2nd Ed. New York: Springer-Verlag. (moderate) Venables, W. and Ripley, B. (2002) Modern Applied Statistics with S. New York: Springer-Verlag. (advanced) Programming Venables, W. and Ripley, B. (2000) S Programming. New York: Springer-Verlag. Chambers, J. (2008) Software for Data Analysis Programming with R. New York: Springer-Verlag. PSDM Event: Open Source Software in Clinical Research June 19th, /28
23 Getting Help in R (cont d) Clinical research Peace, K. and Chen, D.-G. (2010) Clinical Trial Data Analysis Using R. Boca Raton: Chapman and Hall/CRC. More books that use R (or S) can be found at: or PSDM Event: Open Source Software in Clinical Research June 19th, /28
24 R For Clinical Research The Is R Validated? saga: There is the PERCEPTION that a certain three-lettered statistical analysis system is the Gold Standard and, worse, is perhaps the only one accepted by the FDA This is not TRUE! A key aspect of the CT regulatory framework is 21 CFR 11 with respect to digital signatures, audit trails, etc. Questions regarding the applicability of 21 CFR 11 to stand-alone statistical applications as opposed to databases that acquire, store and manage source electronic records PSDM Event: Open Source Software in Clinical Research June 19th, /28
25 R For Clinical Research (cont d) Most decision makers want to see documentation of compliance with applicable aspects of the regulations Efforts to create a guidance document for R began in earnest at user! 2006 conference in Vienna Working Group began drafting a document with the goal of addressing key issues as they specifically pertain to R Marc Schwartz (Vice President, Biostatistics, MedNet Study Solutions) Frank Harrell (Chair at Dept. Biostatistics, Vanderbilt University School of Medicine) Tony Rossini (Group Head, Novartis Pharma AG) PSDM Event: Open Source Software in Clinical Research June 19th, /28
26 R For Clinical Research Leverage existing information on development, version control, testing, maintenance, bug reporting/resolution, stable release cycles, updates, documentation, end user support, etc. received constructive criticism from multiple parties Document submitted to The R Foundation for approval on June 15, 2007 Notified of approval by The R Foundation on July 27, 2007 Available at: PSDM Event: Open Source Software in Clinical Research June 19th, /28
27 R For Clinical Research Covers explicitly listed packages from Base R and the Recommended Packages Does NOT cover other CRAN and non-cran R packages Qualification and Validation Specifically addresses 21 CFR (a-i) and functional requirements PSDM Event: Open Source Software in Clinical Research June 19th, /28
28 R For Clinical Research Changing from the standard to R is possible for clinical research However, it will require time ( learning curve) Time is money! The relevant question is: How much money compared to the money payed annually for licences? PSDM Event: Open Source Software in Clinical Research June 19th, /28
29 Thank you for your attention! PSDM Event: Open Source Software in Clinical Research June 19th, /28
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