Beyond Statistics. Namrata Deshpande, Cytel. Barcelona, PhUSE 2016

Transcription

1 Beyond Statistics Namrata Deshpande, Cytel Barcelona, PhUSE 2016

2 Overview R strengths & challenges GUI with gwidgets Automation with ReporteRs Motivation Concluding remarks PhUSE

3 Why R? Statistical packages for the latest developments in the field Strong graphical packages like ggplot2 Supports Unix, Windows, Mac OS No licensing cost Widely acceptable PhUSE

4 Popularity of R Source: Rexer Data Science Survey April PhUSE

5 Traditional Approach a bit complex! #A program to analyze raw data comparing two treatments # #Inputs Study_name <- "Study1234" #Specify study name data_raw <- read.csv("e:\\data.csv") #Specify the data name Execution through R Inputs part of the Treatment_var <- "Treatment" #Map treatment variable Response_var <- "Response" console actual #Map code response variable #Extracting variables from data Treatment <- data_raw[,treatment_var] Response <- data_raw[,response_var] Sound R programming #Bar plot for mean response library(ggplot2) needed #Load library ggplot2 Mean_resp <- aggregate(response~treatment, #Treatment wise mean FUN = "mean") #response plot1 <- ggplot(mean_resp, #Bar plot aes(x=factor(treatment), y=response, fill=factor(treatment), width = 0.5)) + geom_bar(stat="identity", position= "dodge") + xlab("treatment") + ylab("mean Response") + ggtitle("comparison of Treatments") + scale_fill_discrete(name="treatment") + theme(axis.text.x = element_text(size = 11), axis.text.y = element_text(size = 11)) #Comparison of two treatments tout <- t.test(response~treatment) #Two sample t-test PhUSE

6 Better R Experience PhUSE

7 gwidgets An R package authored by John Verzani Widget Interactive controls on a GUI How does gwidgets work? R gwidgets GUI in R GUI Toolkit e.g. tcltk PhUSE

8 GUI with gwidgets Window and Layout Base container using gwindow [1,1] [1,2] [2,1] [2,2] [3,1] [3,2] Tabular layout using glayout layout[1,1,anchor = c(0,0)] <- widget PhUSE

9 GUI with gwidgets (cont.) Text box and File Browser Add text box with gedit Add labels with glabel Add browser with gfilebrowse PhUSE

10 GUI with gwidgets (cont.) Combo-box and Button Add drop-down list with gcombobox Add buttons with gbutton PhUSE

11 GUI with gwidgets (cont.) Handler functions: Handle interdependent actions on the GUI Call Analysis function PhUSE

12 gwidgets Many more GUI functional as well as cosmetic features multiple tabs radio buttons check boxes add images Simple intuitive functions Enables tool development PhUSE

13 ReporteRs Package authored by David Gohel et al. Generates Well Formatted Reports from R Add Text Add Tables Add Plots PhUSE

14 Reporting with ReporteRs Use Templates addtitle addsubtitle adddate PhUSE

15 Reporting with ReporteRs (cont.) Add text using addparagraph pot for multiple formats Bullet points using set_of_paragraphs PhUSE

16 Reporting with ReporteRs (cont.) Well formatted tables with FlexTable addheaderrow addfooterrow Set column wise width, alignment, etc. PhUSE

17 Reporting with ReporteRs (cont.) Add graph objects using addplot Editable title, labels, legend PhUSE

18 ReporteRs Ability to generate reports from R instantly. Editable graphs and tables Customized formatting Enables end to end automation PhUSE

19 Motivation Tool development for a team of non-statisticians The Problem Constraints Group of Clinicians Limited budget Solution Routine exploratory analysis Issues with manual execution Automate the Process No Programming User friendly R Tool Intuitive UI with gwidgets Automation with ReporteRs PhUSE

20 Motivation Glimpse of Analysis data PhUSE

21 The GUI PhUSE

22 The Report PhUSE

23 The Report PhUSE

24 Concluding Remarks gwidgets, ReporteRs Powerful non-statistical R packages Leverage the strength of statistical & graphical R packages Extend R usage to non-programmers Save time with automation Add sophistication to R s user experience PhUSE

25 Thank you!