{"id":1689,"date":"2016-06-17T21:02:25","date_gmt":"2016-06-17T20:02:25","guid":{"rendered":"http:\/\/pcool.dyndns.org:8080\/statsbook\/?page_id=1689"},"modified":"2025-06-30T18:19:27","modified_gmt":"2025-06-30T17:19:27","slug":"advanced-concepts","status":"publish","type":"page","link":"https:\/\/pcool.dyndns.org\/index.php\/advanced-concepts\/","title":{"rendered":"Advanced Concepts"},"content":{"rendered":"\n

On this page, advanced concepts are discussed for the more experienced user. In particular, the manipulation of data and the assigning \/ arranging of new variables.<\/p>\n\n\n\n

To rearrange \/ group data, it is useful to know several R operators \/ functions.<\/p>\n\n\n\n

R Objects and Operators<\/a><\/p>\n\n\n\n

Common R Functions<\/a><\/p>\n\n\n\n

Helpful R Functions in Packages<\/a><\/p>\n\n\n\n

Defining R Functions<\/a><\/p>\n\n\n\n

Importing and Cleaning Data in R<\/a><\/p>\n\n\n\n

R data manipulation functions examples:<\/strong><\/p>\n\n\n\n

To select a subset of data; for example select different observers (1 and 2) and create a new data frame with data of both observers in columns (the original data frame is called ‘results’ with as variables ‘observer’, ‘rotation’ and ‘outcome’):<\/p>\n\n\n\n

observer1 <- subset(results,observer==1,select=c(outcome, rotation))<\/span>\n names(observer1)[names(observer1)==\"outcome\"]<-'outcome1'<\/span>\n names(observer1)[names(observer1)==\"rotation\"]<-'rotation1'<\/span>\n observer2<-subset(results,observer==2,select=c(outcome,rotation))<\/span>\n names(observer2)[names(observer2)==\"outcome\"]<-'outcome2'<\/span>\n names(observer2)[names(observer2)==\"rotation\"]<-'rotation2'<\/span>\n observers<-cbind(observer1,observer2)<\/span><\/code><\/pre>\n\n\n\n
Some of these functions \/ operators are used in the examples below.<\/p>\n\n\n\n
Printing percentages and currency signs:<\/strong><\/p>\n\n\n\n
To print percentages, use the sprintf function from R. For help on formatting, type ?sprintf<\/span> in the console. A full description is outside the scope of this page. However, the first argument of the sprintf function should be within quotation marks (“). This argument starts with a % sign (to show a variable is coming), is followed by a full stop (to indicate the decimal point), followed by the number of decimal characters followed by an f (for floating point variable) and finally followed %% (the first percent sign is an ‘escape’ character as it would otherwise indicate a variable). The second argument of the function is the variable it should be applied to. Therefore, to print a percentage (%) sign behind a number:<\/p>\n\n\n\n
a <- c(1,2,3,4,5,6,7,8,9)<\/span>\na<\/span>\n[1] 1 2 3 4 5 6 7 8 9<\/span>\nb <- sprintf(\"%.0f%%\",a)<\/span>\nb<\/span>\n[1] \"1%\" \"2%\" \"3%\" \"4%\" \"5%\" \"6%\" \"7%\" \"8%\" \"9%\"<\/span><\/code><\/pre>\n\n\n\n
Similarly, to print a % sign with two decimal places:<\/p>\n\n\n\n
c <- sprintf(\"%.2f%%\", a)<\/span>\nc<\/span>\n[1] \"1.00%\" \"2.00%\" \"3.00%\" \"4.00%\" \"5.00%\" \"6.00%\" \"7.00%\" \"8.00%\" \"9.00%\"<\/span><\/code><\/pre>\n\n\n\n
Finally, to print a \u00a3 sign (for example):<\/p>\n\n\n\n
d <- sprintf(\"\u00a3 %.2f\", a)<\/span>\nd<\/span>\n[1] \"\u00a3 1.00\" \"\u00a3 2.00\" \"\u00a3 3.00\" \"\u00a3 4.00\" \"\u00a3 5.00\" \"\u00a3 6.00\" \"\u00a3 7.00\" \"\u00a3 8.00\" \"\u00a3 9.00\"<\/span><\/code><\/pre>\n\n\n\n
Manipulating dates:<\/strong><\/p>\n\n\n\n
Revalue of map values (factors) with the plyr package1<\/a><\/sup> (for example month names from the first date of the month:<\/p>\n\n\n\n
library(plyr)<\/em><\/span>\nmonth <- mapvalues(activity$ActivityMonth,from=c('01\/01\/2014','01\/02\/2014','01\/03\/2014','01\/04\/2014','01\/05\/2014','01\/06\/2014','01\/07\/2014','01\/08\/2014','01\/09\/2014','01\/10\/2014','01\/11\/2014','01\/12\/2014'),to=c('Jan','Feb','Mar','Apr','May','Jun','Jul','Aug','Sep','Oct','Nov','Dec'))<\/em><\/span><\/code><\/pre>\n\n\n\n
Calculating the ‘day number’ of a date:<\/strong><\/p>\n\n\n\n
datum<-as.Date(as.character('31\/12\/2000'),'%d\/%m\/%Y')<\/span><\/em>\ndatum<\/span><\/em>\n[1] \"2000-12-31\"<\/span><\/em>\n# the date is converted to ISO format<\/a> as recommended\nformat(datum,format='%j')<\/span><\/em>\n[1] \"366\"<\/span><\/em><\/code><\/pre>\n\n\n\n
Convert incorrectly formatted data into appropriately declared variables that allow subsequent analysis:<\/strong><\/p>\n\n\n\n
It is a common error to group variables incorrectly and create a separate variable (column) for each group. However, variables should be in columns and the group is a separate variable. An example is show here<\/a>.<\/p>\n\n\n\n
 Examples:<\/strong><\/p>\n\n\n\n
Please note the ggplot2 package2<\/a><\/sup> will have to be loaded.<\/p>\n\n\n\n
To create a faceted bar chart, load the Diag.rda<\/a> data frame into JGR and run the create faceted bar chart <\/a>function. This will create the following plot:<\/p>\n\n\n\n
\"\"<\/figure>\n\n\n\n
This example shows how to regroup data and create a plot on defined criteria.<\/p>\n\n\n\n
To create a stacked and faceted bar plot, load the SpecGroup.rda <\/a>data frame into JGR and run the stacked faceted bar plot 1 <\/a>function. This will create the following plot:<\/p>\n\n\n\n
\"\"<\/figure>\n\n\n\n
To create a stacked and faceted bar plot where the axes are ‘free’ and only labels that are greater than 1 are displayed; load the TNMstage.rda<\/a> data frame into R and run the stacked faceted bar plot 2<\/a> function. This will create the following plot:<\/p>\n\n\n\n
\"\"<\/figure>\n","protected":false},"excerpt":{"rendered":"
On this page, advanced concepts are discussed for the more experienced user. In particular, the manipulation of data and the assigning \/ arranging of new variables. To rearrange \/ group data, it is useful to know several R operators \/ functions. R Objects and Operators Common R Functions Helpful R Functions in Packages Defining R […]<\/p>\n","protected":false},"author":2,"featured_media":0,"parent":0,"menu_order":0,"comment_status":"closed","ping_status":"closed","template":"","meta":{"inline_featured_image":false,"footnotes":""},"class_list":["post-1689","page","type-page","status-publish","hentry"],"_links":{"self":[{"href":"https:\/\/pcool.dyndns.org\/index.php\/wp-json\/wp\/v2\/pages\/1689","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/pcool.dyndns.org\/index.php\/wp-json\/wp\/v2\/pages"}],"about":[{"href":"https:\/\/pcool.dyndns.org\/index.php\/wp-json\/wp\/v2\/types\/page"}],"author":[{"embeddable":true,"href":"https:\/\/pcool.dyndns.org\/index.php\/wp-json\/wp\/v2\/users\/2"}],"replies":[{"embeddable":true,"href":"https:\/\/pcool.dyndns.org\/index.php\/wp-json\/wp\/v2\/comments?post=1689"}],"version-history":[{"count":6,"href":"https:\/\/pcool.dyndns.org\/index.php\/wp-json\/wp\/v2\/pages\/1689\/revisions"}],"predecessor-version":[{"id":4629,"href":"https:\/\/pcool.dyndns.org\/index.php\/wp-json\/wp\/v2\/pages\/1689\/revisions\/4629"}],"wp:attachment":[{"href":"https:\/\/pcool.dyndns.org\/index.php\/wp-json\/wp\/v2\/media?parent=1689"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}
Create a survival curve from dates<\/a>; a data frame that contains the date of diagnosis and date of failure (example on how to convert dates to follow up time and how to create the censor variable; use survivaldates.rda<\/a> with this example).<\/p>\n\n\n\n