Linear Models in Stata Workshop

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Linear Models are the heart of all statistical modeling.

It’s still one of the most-used statistical procedures and its the basis of many, many types of models.

And yet there is more to running linear models than inputting predictors and an outcome variable into a model.

You need to have clear, precise procedures for:

  • choosing predictors and finalizing the model
  • interpreting and graphing results
  • checking assumptions and knowing when the results are reliable

This workshop will take you through all the steps of setting up, running, testing, and interpreting linear regression and ANOVA in Stata.

You’ll learn the options and short cuts in Stata that will give you the output you need to answer your research question and understand your results.

In short, after taking this workshop, you will be able to run, interpret, graph, and diagnose three types of linear models: linear regression, ANOVA, and ANCOVA in Stata.

Every Live Workshop at The Analysis Factor includes:

✅ 1 year of access to the workshop website
✅ All the data, programming code, exercises and handouts you’ll need
✅ Live webinars and question & answer sessions
✅ Video recordings of all live content for later or repeated review
✅ The opportunity to ask questions live and on workshop web pages


What You Will Learn:

Comparing Groups: T-test, ANOVA,  ANCOVA

There are a number of variations on tests that compare means across groups.  We’ll start with a review of a simple t-test, then move into running one One-way and two-way between subjects factorial ANOVA models.  Special attention will be placed on:

  1. Running the model
  2. Effect Size Statistics
  3. Post estimation commands
    1. simple contrast
    2. partial interaction
    3. interaction contrasts

Basic Regression Analysis

We’ll start once again with something simple: running correlations, and how correlations relate to linear models.  We’ll move on to see a number of useful procedures in Stata for running a linear regression and understanding output in models with just a single predictor.

Useful procedures include:

  1. Post estimation
    1. predicting values
    2. residuals
    3. graphing

Linear Regression with Multiple Predictors

Now we integrate what we’ve covered so far to build more complicated models.  We’ll include the classic linear regression with continuous predictor variables.

We’ll also build on that so you can build very sophisticated linear models.  Many of these topics seem confusing, but we’ll walk you through so you understand them intuitively.

  1. Understanding the different types of predictor variables: continuous, categorical
  2. Creating interactions of each predictor variable type
  3. Fitting polynomials and logs
  4. Finding and using temporarily stored parameters
  5. Centered and standardized coefficients
  6. Computing predicted means using margins command
  7. Graphing predicted means using marginsplot

Model Diagnostics

But is the model any good?  Are assumptions met?

Find out with a clear procedure for checking assumptions and potential data issues, and more importantly, what to do about them:

  1. The impact of predictor variables on the model
    1. partial and semi-partial coefficients
    2. effect size
  2. Testing multiple coefficients using the following commands
    1. test
    2. testparm
    3. lincom
  3. Understanding suppressor variables
  4. Outliers: standardized residuals, leverage, and Cook’s D
  5. Multicollinearity
  6. Nonlinearity
  7. Homoskedasticity
  8. Normality of residuals
  9. Displaying results: display options and formatting
  10. Storing results
  11. Comparing models
    1. Using same sample for all models
    2. estimates store command

Outputting results

Stata has some very nice post estimation commands that allow you to see results in different formats and in direct answer to different ways of posing research questions.  We’ll go through the most useful of these.

Review of data that does not use ordinary least square

And finally, what do you do with response variables that don’t work in linear model.  We’ll finish up with an overview of the options for common variable types:

  1. Count
  2. Bounded
  3. Binary outcome variable
  4. Categorical outcome variable
    1. multinomial
    2. ordinal

But can I keep up?

This is an intermediate level workshop.  It is for researchers, not statisticians.

You should have a solid understanding of introductory statistics (correlation and t-tests should be a review).

You can be relatively new to Stata–we’ll show you all the commands, but you should already know the basics–how to open a data set, run a do file, etc.

You will need to spend some time each week. You will learn concepts and get some clarity if you don’t do the exercises and try to rerun my examples on your own. But you won’t entirely get it.

This is a workshop where you want to get your hands dirty with some data. Please expect to spend 1-2 hours per module just doing the exercises.

This workshop is for you if you:

  • Have run basic statistics, and would like to learn linear models.
  • Have used linear regression or ANOVA, but not in a while and would like a refresher
  • Have learned linear regression or ANOVA in a class, but haven’t done one (or you have, but didn’t feel confident about it). You’d like to the real process on real data.
  • Know you will soon need to implement a linear regression and use Stata
  • Have a license to and are familiar with Stata, but want to learn it better.

This workshop is not for you if you:

  • Are a statistics beginner and have never done any statistics. You should be familiar with correlations, p-values, and t-tests.
  • Don’t have enough time to keep up. Each week will require about 4-6 hours for full participation in workshop sessions, Q&As, and exercises. You will have access to all materials for a full year, but if you want to take advantage of the interactive webinars and the Q&As, it’s ideal to put the time in now.


The workshop is offered as an interactive, live online workshop + Membership Site

The instructor will be conducting the workshop live via webinar. You attend online and listen and speak either by phone or over the internet as you see what is happening on his computer screen. Webinars are highly interactive–you can see Jeff’s screen and ask questions during the session, yet you never have to leave your house or office.

During the webinar sessions, Jeff will present concepts and explain the meaning of the techniques in that module, demonstrate how to implement those techniques in on different examples, and answer your questions.

We’ve also created a workshop site that you have access to. For a year.

The site is our home-base for the workshop. It’s where you’ll find everything you need to support your learning of each module:

  • Video Screenshot recordings of each workshop session made available within 48 hours. Review the material right away, a year later, or while doing the exercises. Or if you need to miss one (or all) of the live sessions, you can still participate on your own schedule.
  • Video Recordings of all Q&A sessions. So if you have to miss one, just submit your questions ahead of time and I’ll answer in the Q&A. Just watch it later.
  • Data files. These are real, true, not-textbook-perfect data files from real research projects we’ve worked on with clients who have graciously allowed us to share them with you. You get full access to use the data to try everything I demonstrate in the workshop and try things on your own.
  • Stata syntax to run and explore all of the examples yourself. You won’t learn it unless you try it. So I’m giving you my syntax so you can see exactly how I got all the output I’m showing you.
  • PDF handouts of the presentation slides, which will be available ahead of each session, on which you can take notes.
  • Exercises. (Yes, homework!). You really need to practice this stuff. Get your hands dirty. So we’re giving you the data to try it on your own with new models to try out. But don’t worry–you won’t be on your own stuck on some coding error that won’t work. I’m also giving you the syntax I used to do the exercises and the answers.
  • A place to submit written questions between sessions. So as you’re reviewing videos afterward (or if you missed a live session), just submit a question.
  • A list of helpful resources and suggestions for further reading. We’re not requiring a text book. But there are definitely some good books and articles out there on this topic, and you will learn the techniques better with a little background reading.
  • Bonus videos. I’ve included a number of videos from some webinars on relevant topics to help jog your memory or clear up misunderstandings. Included are:
    • The First 3 Steps to Performing any Statistical Model: Define and Design
    • Dummy Coding and Effect Coding in Regression Models
    • How to Benefit from Stata’s Bountiful Resources
    • Five Tips and Tricks: How to Make Stata Easier to Use
    • Confidence Intervals
    • An Overview of Effect Size Statistics

You’ll have access for a year to this workshop membership site. So as we add resources, re-record sessions, and answer more questions each time we offer the workshop, you have access to the updated material.

The Instructor:

jeff-meyer-150Jeff Meyer is a statistical consultant and the Stata expert at The Analysis Factor.  He teaches workshops and provides Stata examples for a number of our workshops, including Intro to Stata, Missing Data, and Repeated Measures.

He also runs his own consulting firm, Optimizing Outcomes, which helps non-profits determine the impact of their outcomes.

Jeff has an MBA from the Thunderbird School of Global Management and an MPA with a focus on policy from NYU Wagner School of Public Service.

What Our Students Say About Jeff’s Workshops:

“Jeff Meyer clearly explained how to apply statistical concepts to real life data sets using Stata, my primary programming language. Jeff is an excellent instructor. He explained when and how to use the commands in such a clear and understandable manner. Also, both Jeff and the Analysis Factor team answered my questions completely and promptly. I was also happy to hear that Jeff would be available to answer any questions that we may have for up to a year after the workshop ended! I am so glad that I found Analysis Factor. I also liked the fact that the live webinars are recorded. Every researcher has such a busy schedule, and I wasn’t able to make it to all of them. But because the sessions were recorded, I was able to watch them on my own time and catch up.”

“Having Jeff being able to respond to queries on the spot – via the question box – was a fantastic resource. For off topic questions, which he obviously didn’t have time to address within the lecture, he then separately uploaded ‘answers’ onto the course website. That real-time interaction and feedback was truly invaluable. It honestly felt like we were in a physical classroom, which is the biggest complement I can give.”
Ryan J. Kee

“Mr. Meyer is a very knowledgeable Stata user and works very hard to pass along as much information as he can in the time available.”
Collin Stewart

Full Workshop Investment: $347

We’re sorry but this workshop is not currently enrolling.
Please join our waiting list to receive a notification when it is offered again.

Refund Policy: Your registration fee is fully refundable up to 72 hours in advance. Because enrollment is limited, no refunds will be granted after the program begins.


As with all our programs, your satisfaction is guaranteed. If you participate fully in this workshop–watch, read, and try out everything included–and find you are not satisfied for any reason, we will give you a full refund, no questions asked.

Just notify us within 90 days of purchasing the program.