Introduction to Statistical Computing in Clinical Research Biostatistics 212 Lecture 1.

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Presentation transcript:

Introduction to Statistical Computing in Clinical Research Biostatistics 212 Lecture 1

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 Lab

Course Objectives Introduce you to using STATA and Excel for –Data management –Basic statistical and epidemiologic analysis –Turning raw data into presentable tables, figures and other research products Prepare you for Fall courses Start analyzing your own data

Course details Biostats 212 –1 Unit Course –Satisfactory/Unsatisfactory vs. Grades –7 Sessions – Lecture + Lab, starting August 2

Course details New this year: –In-Person + Online versions of the course –Recorded lectures –Forum

Course details Two “In-Person” Sections: –Lectures – in person (6702), Tuesday 1:15-2:45 –Labs – in person ( ), Tuesday 3:00-4:00

Course details One “Online” Section: –Lectures – Recorded, posted late Tuesday afternoon –Labs – Online Wed 1:30-3:00 New this year, online students only Led by Jen Cocohoba – comments?

Course details Recorded Lectures –Audio + video of lecturer + video of screen –Available same day for viewing –See

Course details Forum –Demo –Post all questions here! TA turnaround time –Before you post, see if it’s already there and answered –Consider turning ON your alerts around lab time…

Course details Course Requirements –Hand in all six Labs (even if late) –Satisfactory Final Project Not required –Reading –Attendance

Course details Grading (only relevant for Master’s and ATCR Credit-Bearing students?) –Letter grades: Standard cutoffs % A 80-89% B 70-79% C 60-69% D <60% or Course Requirements not met: F –Satisfactory/Unsatisfactory >80%Satisfactory

Course details, cont Course Director Mark Pletcher TA’s Naomi Bardach Raymond Hsu Sharon Poisson Monika Sarkar Assistant Course Director Jennifer Cocohoba Lab Instructors Jing Cheng Barbara Grimes Nancy Hills Ann Lazar

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- Using Excel 5- Basic epidemiologic analysis with STATA 6- Making tables and figures with STATA 7- Advanced Programming Topics

Overview of labs Lab 1 – Load a dataset and analyze it Lab 2 – Learn how to use do and log files Lab 3* – Import data from excel, generate new variables and manipulate data, document everything with do and log files. Lab 4 – Using and creating Excel spreadsheets Lab 5* – Epidemiologic analysis using Stata Lab 6 – Making a figure with Stata Last lab session will be dedicated to working on the Final Project * - Labs 3 and 5 are significantly longer and harder than the others

Overview of labs, cont Official In-Person Lab time is 3:00-4:00 on Tuesday, but we will start right after lecture, and you can leave when you are done.

Overview of labs, cont Labs are due the following week prior to lecture. Labs turned in late (less than 1 week) will receive only half credit; after that, no points will be awarded. However, ALL labs must be turned in to pass the class (even if no points are awarded). Lab 1 is paper Labs 2-6 are electronic files, and should be ed to your section leader’s course address: (Elizabeth/Raman) or (David/Yvette)

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.

Course Materials Online Syllabus ( –Lectures and Labs/Datasets (“just in time”) –Miscellaneous handouts –Final Project

Getting started with STATA Session 1

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)

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

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

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

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

Demo #1 Open the program Entering vs. loading data Look at data Run a command Orient to windows and buttons

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

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

STATA - Menus Almost every command can be accessed via menu

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

Demo #2 Load a STATA dataset Explore the data Describe the data Answer some simple research questions –Gender, BMI, blood pressure

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

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

STATA commands Graphical exploration – continuous data histogram varname –Simple histogram of your variable graph box varlist –Box plot of your variable qnorm varname –Quantile plot of your variable to check normality

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

STATA commands Analytic statistics – 2 categorical variables

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

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

STATA commands Analytic statistics – 1 categorical, 1 continuous

bysort catvar: summarize [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

STATA commands Analytic statistics – 2 continuous

scatter [var1] [var2] –Scatterplot of the two variables pwcorr [varlist] [, sig] –Pairwise correlations between variables –“sig” option gives p-values spearman [varlist] [, stats(rho p)]

In Lab Today… Expect some chaos! –IT will be here to help with wireless, logins, etc Familiarize yourself with Stata Load a dataset Use Stata commands to analyze data and fill in the blanks

Next week Do files, log files, and workflow in Stata Find a dataset!

Website addresses Course website – Computing information – computinghttp:// computing Download RDP for Macs (for Stata Server) – Citrix Web Server – Stata 12 Server –