Experimental epidemiology analyses with R and R commander. Lars T. Fadnes Centre for International Health University of Bergen

Transcription

1 Experimental epidemiology analyses with R and R commander Lars T. Fadnes Centre for International Health University of Bergen 1

2 Click to add an outline 2

3 How to install R commander? - install.packages("rcmdr", dependencies=true) - - Download necessary web files put them in a folder: Fieldtrials12.RData Exercises-for-the-exp-epi rtf 3

4 Installation of RcmdrPlugin.Cih.Epi Install R (if not done already) Install package Rcmdr (if not done already) Package Install package scroll down to Rcmdr click OK Install package Epi Package Install package scroll down to Rcmdr click OK Download RcmdrPlugin.Cih.Epi from Install package(s) from local zip file (choose the package you just downloaded) Open program Load package Rcmdr Tools -> load Rcmdr plug-in(s) RcmdrPlugin.Cih.Epi click ok and Yes Now you are ready 4

5 Aim for this session Introduce a brilliant tool Analyse a dataset with the tool Guide to further knowledge 5

6 What is R? R is a free software environment that includes a set of base packages for graphics, math, and statistics. You can make use of specialized packages contributed by R users or write your own new functions. 6

7 Why R? Very powerful Developing extremely quickly Working on different platforms (not only Microsoft Windows ) Free of all costs 7

8 Why don t all use R? Click to add an outline 8

9 What is R commander? 9

10 Why R commander? Powerful Free of all costs Working on different platforms (not only Microsoft Windows ) Easy to learn and to use 11

11 How to install R? For Windows: Easy If here at UiB, the IT department will fix it for you if you just ask them to add it for you For Linux (Ubuntu etc): - Very Easy - Just search for R-base-core in Synaptic Package Manager and add it - (also contains a good description for installation on Mac) 12

12 How to install R commander? - Is already installed on UiB computers - - If not: install.packages("rcmdr", dependencies=true) 13

13 Some things to note first R is case-sensitive help, Help, HELP and HELF are different Recommendation: Choose one style and stick to it If it s something you don t know? There are lot s of good information on the web Particularly for R 14

14 Open R Load packages Rcmdr How to start? or write library(rcmdr) 15

15 Menu File Menu: items for loading and saving script files; for saving output and the R workspace; and for exiting Edit Menu: items (Cut, Copy, Paste, etc.) for editing the contents of the script and output windows. Data Submenus containing menu items for reading and manipulating data. Statistics Submenus containing menu items for a variety of basic statistical analyses. 16

16 Menu Graphs Menu items for creating simple statistical graphs. Models Menu items and submenus for obtaining numerical summaries, confidence intervals, hypothesis tests, diagnostics, and graphs for a statistical model, and for adding diagnostic quantities, such as residuals, to the data set. Distributions Probabilities, quantiles, and graphs of standard statistical distributions (to be used, for example, as a substitute for statistical tables) and samples from these distributions. Tools Menu items for loading R packages unrelated to the Rcmdr package (e.g., to access data saved in another package), and for setting some options. Help Menu items to obtain information about the R Commander (including this manual). As well, each R Commander dialog box has a Help button (see below). 17

17 Script Window R commands generated by the R Commander You can also type R commands directly into the script window or the R Console The main purpose of the R Commander, however, is to avoid having to type commands. Output Window Printed output Messages Window Displays error messages, warnings, and notes Graphics Device window When you create graphs, these will appear in a separate window outside of the main R Commander window. 18

18 Available functions: 19

19 Click to add title 20

20 Save dataset under your documents folder Files and documents are available at 21

21 Let s get started Change directory (under File) Find the folder where you placed your data file Import data Give it the name: fieldtrials Save workspace as Give a name to your file The file contains the dataset and any models you might have generated 22

22 Data Types Vectors Quantitative difference (one vs. two apples) including continuous (numerical) variables Number variables coded as vectors as default Factors Qualitative difference (apples vs. pears) Categorical Text variables coded as factors as default Matrices, lists, arrays and data frames 23

23 Variables in dataset - define the datatypes id id number gender male/female - (factor) treatmentarm Treatment (1=zinc, 0=placebo) - (factor) childage Age of the child in months - vector breastfed Is the child breast fed - (factor) lentils Does the child eat lentils? (0=no, 1= yes) - (factor) meat Does the child eat meat? (0=no, 1= yes) - (factor) duration Duration of diarrhea in days - vector diarsev Severe diarrhoea 10 stools per day - (factor) fever Did the child have fever at enrollment? - (factor) clusterzn2/4/8/16 cluster variables identifying living areas 24 - coded as vector, but needs to be transformed into a factor

24 How to save? Save R workspace as This will save your data (in the R format) Save output as This will save your output Another strategy is to cut and paste what you want to save Always save the commands (syntax) essential if you want to re-run the analyses later WordPad is a better option than Word etc (does not autocorrect - change to upper case etc) 25

25 How to write and a command? Simply write the command in the script window, mark it and click Submit or press Ctrl+R 26

26 Nice to know: When writing comments in the syntax, start with the following sign # R will then not consider the line as a command If you are uncertain about a function, use google or help(name-of-function) 27

27 Cluster has numbers and is as default coded as vector, but needs to be recoded into a factor (categorical variables for grouping etc) 28

28 Now we re ready to answer some scientific questions 29

29 Compute new variable Child age in years Child age now given in months of vaccination is often calculated by measuring antibodies before and after vaccination childageyear = childage/ 12 30

30 Does the new variable look reasonable? View data set 31

31 Summarize variable Calculate mean, median and standard deviation for childageyear for each intervention arm (treatmentarm) Numerical summaries 32

32 Doing calculations for subsets by generating new datasets 33

33 Placebo: Zinc: treatmentarm == "placebo" treatmentarm == "zinc" Make the other subset by changing the syntax and run ('Submit') the syntax zinc <- subset(fieldtrials3, subset=treatmentarm=="zinc") placebo <- subset(fieldtrials3, subset=treatmentarm=="placebo") 34

34 You can now easily change between the datasets 35

35 Make a histogram of childageyear First for the 'zinc' dataset Then for the 'placebo' dataset Are they look similar? Note: The histograms will be printed in the R window (not inside R commander) Right click on the graph and you can copy it as metafile to paste it into a document, print it or save it 36

36 Does it look normally distributed? frequency placebo$childageyear 37

37 Box plot Box plot for childageyear By treatmentarm (first remember to select the complete fieldtrials dataset) childageyear placebo treatmentarm zinc 38

38 Is the baseline child age different in the zinc and placebo arms? This can be checked with a robust test not assuming normal distribution? Check with a non-paramethric» two-sample wilcoxon test (log rank test)» Use the Exact test 39

39 Recoding variables Diarrhoea duration can be recoded into an additional categorised variable (diarlong) Data manage variables value = factor Factor can be either number or word value, value, value = factor Listed with comma value:value = factor From lowest to highest values else all other values NA missing 40

40 Click to add title 41

41 Are there differenses in syntax between R and R commander? Some few: Commands that extend over more than one line should have the second and subsequent lines indented by one or more spaces or tabs; all lines of a multiline command must be submitted simultaneously for execution. Commands that include an assignment arrow (<-) will not generate printed output, even if such output would normally appear had the command been entered in the R Console [the command print(x <- 10), for example]. On the other hand, assignments made with the equals sign (=) produce printed output even when they normally would not (e.g., x = 10). Commands that produce normally invisible output will occasionally cause output to be printed in the output window. This behaviour can be modified by editing the entries of the log-exceptions.txt file in the R Commander s etc directory. Blocks of commands enclosed by braces, i.e., {}, are not handled properly unless each command is terminated with a semicolon (;). This is poor R style, and implies that the script window is of limited use as a programming editor. For serious R programming, it would be preferable to use the script editor provided by the Windows version of R itself, or even better a programming editor. 42

42 True or false quiz R commander only works for Ms Windows? R is case sensitive (difference with small and large letters) R is built by a few people with a secret source-code? R was the program that gave their shareholders most profit last year? There are a lot of enthusiastic people working with R providing help to their peers in the R forum? 43

43 R help forum: 44

44 Further reading: The R Commander A Basic-Statistics Graphical User Interface to R - John Fox 2005.pdf Getting started with the R Commander: a basic-statistics graphical user interface to R Quick-R: magnificent guide

45 You have learnt some basic skills and can now experiment with the program yourself 46

46 Questions and comments Click to add an outline 47