1. Introduction to Statistical Computing in Clinical Research Biostatistics 212

2. Today... Course overview –Course objectives –Course details: grading, homework, etc –Schedule, lecture overview Where does Stata fit in? Basic data analysis with Stata Stata demos

3. Course Objectives Learn how to use STATA Learn practical application of basic epidemiological and statistical concepts using STATA Learn how to turn raw data into presentable tables and figures

4. Course details Introduction to Statistical Computing - 1 unit Summer schedule – 2 lectures, 1 lab - Parnassus 9/6 lecture 1-2:30 9/13 lecture 1-2:30, lab 2:45-4:45 Fall schedule – Every other Tuesday – China Basin 9/20, 10/4, 10/18, 11/1, 11/15, 11/29 Lecture 3-4, Lab 4-5 Final Project due 12/6/05

5. Course details Introduction to Statistical Computing - 1 unit Grading: Satisfactory/Unsatisfactory Requirements: -Hand in all four Labs (even if late) -Satisfactory Final Project -80% of total points Reading: Optional

6. Course details, cont Faculty Mark Pletcher, MD, MPH 514-8008 mpletcher@epi.ucsf.edu Lee Zane, MD, MAS zanel@derm.ucsf.edu Scott Biggins, MD 502-5259 sbiggins@pol.net Course email for homework: Bio212ucsf@yahoo.com

7. Overview of lecture topics 1- Introduction to STATA 2- Do files, log files, and workflow in STATA 3- Generating variables and manipulating data with STATA 4- Basic epidemiology with STATA I 5- Basic epidemiology with STATA II 6- Using Excel 7- Organizing a project, making a table 8- Making a figure with STATA or Excel First 2 lectures here at Parnassus, the rest in China Basin

8. Overview of labs Lab 1 – Load a dataset and analyze it, learn about do and log files. Lab 2 – Import data from excel, generate new variables and manipulate data, document everything with do and log files. Lab 3 – Epidemiologic analysis using Stata Lab 4 – Using and creating Excel spreadsheets Labs 2 and 3 will be spread across several lab sessions Course is front-loaded – last 2 lab sessions dedicated to Final Project

9. Overview of labs, cont First lab will be at Parnassus next week 2:45-4:45, the rest at China Basin 4:00-5:00 after lecture Scott Biggins will lead 1 section, I will lead the other China Basin Computer Lab –No computers in it! –Must bring own laptop with Stata loaded

10. Overview of labs, cont Labs are generally due 1 week after the last lab session dedicated to them Labs 2-4 and the Final Project should be emailed to the course email address – bio212ucsf@yahoo.com. Answers posted 1 day after Lab is due If you don’t turn the lab in on time, you STILL must turn it in to pass the class, even though you won’t get points credit for it (per TICR policy). PLEASE CORRECT YOUR COURSE OVERVIEW FORM

11. Final Project Create a Table and a Figure using your own data, document analysis using Stata. Due 1 week after last lab session, 20 points docked for each 1 day late.

12. Getting started with STATA Session 1

13. Types of software packages used in clinical research Statistical analysis packages Spreadsheets Database programs Custom applications –Cost-effectiveness analysis (TreeAge, etc) –Survey analysis (SUDAAN, etc)

14. Software packages for analyzing data STATA SAS S-plus, and “R” SPS-S SUDAAN Epi-Info JMP MatLab StatExact

15. Why use STATA? Quick start, user friendly Immediate results, response You can look at the data Menu-driven option Good graphics Log and do files Good manuals, help menu

16. Why NOT use STATA? SAS is used more often SAS does some things STATA does not Programming easier with S-plus Complicated data structure and manipulation easier with SAS Epi-info is even easier than STATA?

17. STATA – Basic functionality Hold data for you –Stata holds 1 “flat” file dataset only (.dta file) Listen to what you want –Type a command, press enter Do stuff –Statistics, data manipulation, etc Show you the results –Results window

18. Demo #1 Open the program Load some data Look at it Run a command

19. STATA - Windows Two basic windows –Command –Results Optional windows –Variable list –History of commands Other functions –Data browser/editor –Do file editor –Viewer (for log, help files, etc)

20. STATA - Buttons The usual – open, save, print Log-file open/suspend/close Do-file editor Browse and Edit Break

21. STATA - Menus Almost every command can be accessed via menu

22. Demo #2 Enter in some data Look at it Run a couple of commands

23. Menu vs. Command line Menu advantages –Look for commands you don’t know about –See the options for each command –Complex commands easier – learn syntax Command line advantages –Faster (if you know the command!) –“Closer” to the program –Only way to write “do” files Document and repeat analyses

24. STATA commands Describing your data describe [varlist] –Displays variable names, types, labels list [varlist] –Displays the values of all observations codebook [varlist] –Displays labels and codes for all variables

25. STATA commands Descriptive statistics – continuous data summarize [varlist] [, detail] –# obs, mean, SD, range –“, detail” gets you more detail (median, etc) histogram varname –Simple histogram of your variable ci [varlist] –Mean, standard error, and confidence intervals –Actually works for dichotomous variables, too.

26. STATA commands Descriptive statistics – categorical data tabulate [var] –Counts and percentages –(see also, table - this is very different!)

27. STATA commands Analytic statistics – 2 categorical variables

28. tabulate [var1] [var2] –“Cross-tab” –Descriptive options, row(row percentages), col(column percentages) –Statistics options, chi2(chi2 test), exact(fisher’s exact test)

29. Getting help Try to find the command on the pull-down menus Help menu –If you don’t know the command - Search... –If you know the command - Stata command... Try the manuals –more detail, theoretical underpinnings, etc

30. STATA commands Analytic statistics – 1 categorical, 1 continuous

31. bysort catvar: sum [contvar] –mean, SD, range of one in subgroup ttest [contvar], by([catvar]) –t-test oneway [contvar] [catvar] –ANOVA table [catvar] [, contents(mean [contvar]…) –Table of statistics

32. STATA commands Analytic statistics – 2 continuous

33. scatter [var1] [var2] –Scatterplot of the two variables pwcorr [varlist] [, sig] –Pairwise correlations between variables –“sig” option gives p-values

34. Demo #3 Load a STATA dataset Explore the data Describe the data Answer some simple research questions

35. Next week Do files, log files, and workflow in Stata In lab next week: –Familiarize yourself with Stata –Practice today’s material (loading and analyzing data) –Start learning how to use do and log files You can leave lab early if you finish!