IT’S TIME TO FINALLY UNDERSTAND LOGISTIC REGRESSION.

"I’m so glad I came across [this] site and registered for this workshop. I’m sure I’ll be registering for more workshops in the future!

The cost-benefit for this workshop is incredible! You just can’t beat it!"

— Paula Fleshman, PhD, Education Research Consultant
Logistic Regression Student

Sooner or later, you’re going to have to answer a research question with a categorical dependent variable:

• Are bilingual speakers more likely to make pronunciation mistakes than native speakers under conditions of cognitive load?
• Did a physical therapy intervention improve the likelihood that athletes with a knee injury were able to return to play within the same season?
• Do nutrition protocol and a physical therapy intervention affect whether patients can perform each of a set of tasks post-surgery?

As you may have already encountered, no matter how many ways you transform or try to finagle the data, you just can’t force it into a linear regression or ANOVA.

So what do you do?

Logistic regression: A researcher’s best friend when it comes to categorical outcome variables.

Maybe you’ve avoided logistic regression before because it’s seemed quite complex or overwhelming… or simply because it wasn’t a required part of your previous statistics coursework.

It’s time to get you over that barrier.

Yes, understanding logistic regression will require some new statistical concepts, but we assure you:

If you can use linear models, you can understand logistic regression (really!).

Introducing…

Logistic Regression:
Binary, Ordinal and Multinomial Outcomes

A 4-Module Online, Live Interactive Workshop

STARTS TUESDAY, JUNE 6, 2017

"…You really get the method at a fundamental level, but not in a way disconnected from the grit of actual practice… Karen strikes the perfect balance of theory and practice."

— Fred Petillo, MS, MBA, Market Research Manager, State Bar of Wisconsin
Logistic Regression Student

I’m Karen Grace Martin, your workshop instructor for Logistic Regression. My goal is that by the end of the workshop, you will be able to recognize the need for, conduct, evaluate, and interpret a logistic regression model, as well as use it to predict outcome probabilities.

In this four-module live, online workshop, you’ll learn the similarities and differences between linear and logistic regression for three kinds of categorical variables:

• Binary (two categories)
• Multinomial (three or more unordered categories)
• Ordinal (three or more ordered categories)

All those concepts unique to logistic regression, like information criteria, maximum likelihood, deviance, logit links, odds ratios, and ROC curves? We’ll go over those in detail.

After this course, you will fear no categorical dependent variable!

"… Karen has a gift for teaching this material in a way that is clear and accessible to everyone."

— Jason Hurwitz, PhD, Assistant Research Scientist
College of Pharmacy, University of Arizona
Logistic Regression Student

Who Is This Workshop For?

This workshop is for you if:

• You’ve attempted a logistic regression before, but found it confusing or difficult, and you didn’t really understand it
• You have used linear regression or ANOVA and now want to expand your knowledge
• You know you’ll soon be faced with the need to implement a logistic regression and want to know how to proceed

It’s not for you if:

• You’re new to statistics or regression and ANOVA (You’ll need a solid background in statistics. See below for more details on the course prerequisites.)
• You don’t have time to keep up with the coursework. (To participate fully, please be prepared to invest 5-10 hours per week for workshop sessions, Q&A, and exercises. While you can revisit the material any time during the next 12 months, if you want to take full advantage of the live components, set aside time NOW.)

"It’s been a long time since I looked at log reg. I was concerned I wouldn’t keep up… but I kept up far more than I thought I would, and that’s because Karen is a great, great lecturer."

— Fred Petillo, MS, MBA, Market Research Manager, State Bar of Wisconsin
Logistic Regression Student

How Does It Work?

This course is a 4-module live, interactive online workshop.

All sessions are conducted online via live webinar. You can log in via phone or Internet. You’ll see the instructor’s screen to view the presentation, all from your own home or office.

During each webinar session, the instructor will present concepts and explain the meaning of the techniques in that module, then demonstrate how to implement those techniques, test the model, and interpret the results.

Each session, there will also be plenty of time to ask your own questions.

Have more questions? No problem!

In addition to the four live webinar sessions, you’ll also meet with your instructor and our software teaching assistants for three additional Q&A sessions where you can get additional assistance on workshop concepts, deepen your knowledge, and clarify any questions.

All 4 Workshop Modules and 3 Q&A Sessions Are Recorded for Your Convenience.

As a participant in the Logistic Regression workshop, you’ll have access to a participant-only website, your workshop "hub." That’s where you’ll access all workshop resources and material, including:

• SPSS, SAS, Stata, and csv data files.

  These are real, true, not-textbook-perfect data files from real research projects I’ve worked on with clients, who have graciously allowed me to share them with you. You get full access to use the data to try everything I demonstrate in the workshop to try things on your own.

• SPSS, SAS, Stata, and R syntax code to run and explore all of the examples.

  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.

• Video demonstrations in SPSS, SAS, Stata, and R.
  

  We provide pre-recorded software-specific video demonstrations of all the examples covered in each workshop module, including answers to the exercises based on that software.

• PDF handouts of presentation slides.

  Made available ahead of each session so you can download, print out, and take notes as you follow along.

• Video screen capture recordings of each workshop session.

  Made available within 48 hours after each session so you can review the material at your convenience.

• Exercises. (Yes, HOMEWORK!)

  You really need to practice this stuff and get your hands dirty, so we’re giving you the data to try it on your own with new models. But don’t worry — you won’t be on your own stuck on some coding error that won’t work. You’ll also get the syntax we used to do the exercises and the answers.

• A place to submit written questions between sessions.

  Got a question as you’re reviewing the video recording or your notes? Just submit a question on the workshop website. I’ll answer it there if I can, or if it’s something I need to show you, I’ll answer it in the next Q&A session.

• Video recordings of all Q&A sessions to review at your convenience.

• A list of helpful resources and suggestions for further reading.

  There’s no required textbook, but there are some good books and articles on this topic, and you’ll learn the techniques better with some background reading. The list is available when you first register, so you have time to request them through inter-library loan if necessary.

• 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:

  – A Review of Logarithms for the Data Analyst
  – What Happened to R Squared?: Assessing Model Fit for Logistic, Multilevel, and Other Models That Use Maximum Likelihood
  – Understanding Probability, Odds, and Odds Ratios in Logistic Regression Models
  – ROC Curves

You’ll have access to this site and all the related materials and resources for ONE FULL YEAR. That means you can re-watch sessions, ask additional questions, and attend the course again during that 12-month period.

Often, our students report they understand the material at a deeper level on a second or third pass. This stuff is not easy. You’ll learn more every time, so take advantage of it!

"Karen is a brilliant presenter. She has a very good command of the subject matter and is able to present complicated material in a way that is easy to understand, while at the same time conducting the workshops in a professional manner."

— Philip O’Sullivan, Senior Policy Advisor, Insurance Council of Australia
Logistic Regression Student

What’s Covered in the Workshop?

Module 1: The Binary Logistic Regression Model

This module lays the foundation for logistic regression. We’ll start with a review of linear models, then walk through differences and similarities to logistic models. We’ll talk in detail about why the logistic model is necessary and what a logit link really means. Next, we’ll review probabilities and odds and what they really measure. Then we’ll end with a simple example, and walk through what the model tells us about the relationships between predictors and our categorical outcome.

• A brief review of the linear regression model, why it does not work for categorical data, and why logistic regression does
• The similarities and differences between the linear and logistic models
• Link functions, the logit function, probability and odds, and how they are used in logistic regression
• Model assumptions
• Interpreting coefficients, odds ratios, relative risks, and confidence intervals, including odds ratios for categorical predictors and interactions
• Demonstrations in SAS, R, Stata and SPSS (pre-recorded)

Module 2: Fitting and Evaluating the Model

Now that we’ve got a solid understanding of the model, we’ll learn ways of evaluating it. Is it any good? Does it fit the data? How well does the model predict outcomes? What happened to R-squared?

• Maximum Likelihood estimation: what it means and how it affects model fit statistics
• Evaluating the model as a whole using Likelihood Ratio Tests, Deviance, Information Criteria, and Pseudo R-Squared statistics
• Using the model to predict probabilities and classify individuals with classification tables
• Evaluating the predictive ability of the model using ROC Curves and Hosmer-Lemeshow Goodness of Fit tests
• Demonstrations in SAS, R, Stata and SPSS (pre-recorded)

Module 3: Using and Assessing the Model to Predict Outcomes

Once we know a model as a whole is working, we can then investigate in detail the effects of individual predictors. There are various ways to do so: graphing, calculating predicted probabilities and examining odds ratios. Odds ratios in particular are bizarre, but you can learn them. We’ll spend a lot of time on interpreting them, especially for interactions, which get even trickier.

• Evaluating each predictor using Likelihood Ratios and Wald Statistics
• A step-by-step of how to use the estimated coefficients to calculate predicted probabilities and use them to interpret effects of predictors
• Interpreting odds ratios for interaction effects
• Model assumptions and dealing with data fitting challenges, including complete separation, zero cell counts, and influential points
• Demonstrations in SAS, R, Stata and SPSS (pre-recorded)

Module 4: Ordinal and Multinomial Models

Everything we’ve done up to this point has been about binary models, as they’re the foundation of logistic regression. Good news: Everything we do in binary logistic models can be expanded to multinomial and ordinal categorical outcomes, so that’s our focus for this module.

• Differences and similarities between the multinomial model and the binomial model
• The different procedures in SAS, R, SPSS and Stata you need to run multinomial models
• The difference between ordinal models for 3 or more ordered categories and multinomial models for 3 or more unordered categories
• The big effect that software default settings can have on your results
• The proportional odds assumption
• Demonstrations in SAS, R, Stata and SPSS (pre-recorded)

The Details

There are 4 live webinar sessions in this workshop. In order to keep momentum going while giving you enough time to keep up, we’ve devised this schedule based on feedback from previous participants:

We’ll meet for two weeks in a row — beginning June 6, 2017. This compacted schedule allows you to fit the workshop into any other summer plans you may have.

We will meet on Tuesdays & Thursdays at 1 PM, US Eastern. The workshop sessions are approximately 2 hours long, including time for questions.

We will also meet for three Q&A sessions throughout this time. We will meet at 1 PM (US Eastern) on the following dates:

Remember, everything is recorded and available for you to watch at your convenience, should you be unable to attend a live session.

Also, you have access to all the class materials for a full 12 months from your enrollment date.

Pay in full or in 3 installments of $133. (Your first installment will be billed today. Then your credit card will be billed automatically every 30 days for the remaining 2 installments.)

Every Live Workshop from 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 to submit questions to be answered between sessions

"Karen did an amazing job presenting, teaching, allowing participants to ask questions, answering questions, and keeping the workshop on pace. She explained the theory well in laymen’s terms and made me feel comfortable at my level of understanding. The prep work and homework were also on point, guiding one through necessary steps and thinking processes for the analyses learned. The live Q&A sessions were very helpful as well!!

— Paula Fleshman, PhD, Education Research Consultant
Logistic Regression Student

About Your Instructor

I’m Karen Grace-Martin, your workshop instructor.

As president and founder of The Analysis Factor, I’ve been supporting researchers like you through their statistical planning, analysis, and interpretation since 1997.

With masters degrees in both applied statistics and social psychology, I’ve been honored over the past 15 years to work with everyone from undergrad honors students to Cornell professors, and from non-profit evaluators to corporate data analysts.

After seeing so many smart people get nervous, uncertain, and downright phobic about analyzing their data, I made it my mission to remove the barrier between research and statistical analysis.

I want to banish the "stats speak" that makes eyes glaze over, and instead explain statistical terminology in plain English.

My goal is to help you improve your statistical literacy so you can bring your important research results into the light with confidence.

Our Software Teaching Assistants

Kim Love is the owner of and lead consultant at K.R. Love Quantitative Consulting and Collaboration.

As a software teaching assistant for this workshop, Kim will create the R demonstrations and code to use in the examples and exercises. She will attend the live Q&A sessions and monitor the workshop website to answer your R questions.

She has worked as a statistical consultant and collaborator in multiple professional roles, most recently as the associate director of the University of Georgia Statistical Consulting Center. Kim has a B.A. in mathematics from the University of Virginia, and an M.S. and Ph.D. in statistics from Virginia Tech.

Jeff Meyer is a statistical consultant, instructor, and writer for The Analysis Factor, specializing in Stata.

As a software teaching assistant for this workshop, Jeff will write the Stata code to use in the examples and exercises and make the Stata video demonstrations. He’ll also attend the live Q&A sessions and monitor the workshop website to answer any Stata questions you have.

He has an M.B.A. from the Thunderbird School of Global Management at Arizona State University and an M.P.A. with a focus on policy from the Wagner School of Public Service at New York University.

"Your explanations are clear and precise, you always answered all questions that were asked during the sessions, and I never felt belittled or stupid asking a question. You are an exemplary teacher."

— Barbara Hanna, Logistic Regression Student

Prerequisites

So what kind of background in statistics do you need?

This workshop is for researchers, not statisticians. That being said, it is an INTERMEDIATE LEVEL WORKSHOP.

You should have solid experience running linear models (ANOVA and/or linear regression), including a basic understanding of:

• Least-squares estimation
• Dummy variables
• Interactions

Be prepared to do a bit of algebra and equation solving.

You’ll get the most from this workshop if you have:

• MINIMUM two statistics classes, including some experience in data analysis, particularly linear modeling.
• Familiarity with using a statistical software package. Examples, data sets, and code will be provided for SPSS, SAS, Stata and R.

An additional word about software packages:
This workshop focuses on the concepts, steps, and interpretation of logistic regression — it is not about the software. While I am familiar with Minitab and JMP and will do my best to answer software questions, I’m not familiar with the intricacies and defaults of every software program out there. However, if YOU are familiar with another package and are comfortable reading the manual to understand the defaults in its logistic regression procedure, you’ll be fine.

If you have questions about whether you’re ready for this class, just email us. We’ll give you our honest opinion. We want you to succeed!

"The Analysis Factor does a great job, and I really like the applied approach. For me it connects the theory with practice and reinforces the concepts."

— Leo Lillard, Coaching with Clarity
Logistic Regression Student

Your Satisfaction Is Guaranteed

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.

FAQs

Q. Will I be able to keep up?

A. If you meet the prerequisites listed above and can set aside the suggested time (4-6 hours per module reviewing the concepts and doing the exercises, and re-running class examples on your own), you should be fine.

You know how this goes: The more time you put in, the deeper your understanding.

Q. What’s your refund policy?

A. Your registration fee is fully refundable up to 72 hours before your first class session. No refunds will be granted after the program begins.

Q: Do you offer student discounts?

A: Yes, we do! Current students with a valid ID can register for almost 40% off the standard rate. Click here to receive our student discount on this and future workshops.

Q: Will you offer SAS support in this workshop?

A: Yes, we’ll have support for SPSS, R, Stata and SAS.

Q. I don’t use any of those packages. What about the rest of us?

A: You may be fine, even if you use another stat package. Yes, we’re supplying code for SPSS, R, Stata and SAS, but the focus of the workshop is on the steps to take and what it all means. Those, as well as the logic, are the same across all software packages.

You may have to work a little harder to implement the exercises and to translate it into the software you use.

If you’re using another program and are comfortable working in that program and figuring out a new procedure, the workshop will fill in the concepts, vocabulary, and steps.

If you’re still learning that other program, this might be too hard, unless you have a lot of time and willingness to figure things out.

Q: Things are very busy at work right now, and I’m afraid I won’t have time to keep up. How much time per week does this really take?

A: We’ve worked really hard to make sure people can do the workshop in the midst of their normal work life.

Each workshop instruction session is about two hours, whether you attend live or listen to the recording. We know it’s hard to attend 4 weeks in a row at the same time, so we have created a two-week/four-module schedule to help you "get in and out" and back to your regular responsibilities.

We also have three, one-hour Q&A sessions. You don’t have to attend; they’re available so you can have any questions answered or listen in on others’ questions.

We provide exercises, answers and data sets, so you can practice what you’ve learned each week and get help in the Q&As. These will take you a few hours each week, maybe up to 5 or so. The exercises aren’t required — you’re not graded. But we’ve gotten feedback that they’re very helpful, as it allows you to practice and figure out what you did and didn’t understand.

In other words, in the three weeks the course covers, there are 8 hours of class time, 3 hours of Q&A, and about 15-20 hours of practice time. So if you have a crazy hectic month ahead, you may be better off waiting to take the class as you won’t really have a chance to catch up.

One reminder: You have access to the workshop website, all materials, and a place to ask questions for a year. So if you get behind, you aren’t missing out. You can catch up on your schedule.

Q: I teach/work/sleep during this time/live outside the U.S and cannot attend live. Is there any way to register and access the webinar sessions later?

A: Yes! We have participants from many time zones with many different work schedules. In order to support our diverse student base, all workshop sessions – including the modules and Q&A’s — are recorded and made available to students within 48 hours. They’re screenshot video files, so you’ll hear me talking and see my screen, just as live participants do. You can even submit questions for written answers any time between sessions. Many students take the entire workshop in this manner, never attending a session live.

You can also download and keep these videos forever, so if you need to refresh your memory at any point in the future, it’s yours to review.

Q: I’m outside the U.S. Can I still participate?

A: Yes. We have participants in our workshops from many different countries. You will want a fast Internet connection and either a computer speaker or a telephone if you plan to attend live.

Q: Can I pay with Paypal?

A: Yes. When you check out, you can pay directly using our system or paying with Paypal.

Q: Can I join the Q&A webinars from my iPad or iPhone?

A: Yes. Thanks to a new upgrade to GoToWebinar, attendees now have the option of registering and joining the workshop Q&A sessions from your Apple or Android device by downloading a free GoToMeeting app.

Q: This really isn’t a good time for me. Will you be offering this workshop again soon?

A: Yes, we’ll offer it again, but it’s not scheduled yet. We tend to run this workshop once per year. Remember, though, that you can sign up now and get access to all the course materials (live trainings, support, exercises, the option to ask questions, and live Q&A sessions, as well as any additional bonuses). I would suggest registering now. You’ll get all the materials to download and review at your convenience.

Registering now will give you complete access to the website and all materials for one year. Plus, ongoing support is included through access to the workshop website for a full year.

Q. What software do you support for this class?

A: SPSS, SAS, Stata, and R. Instruction sections will focus on concepts, steps to run a model, and interpretation of output regardless of software. For each software package, we will provide:

• Pre-recorded software-specific video demonstrations of all the examples covered in each workshop module
• Syntax to run those examples
• Syntax to run the exercises
• Answers to the exercises based on that software

Stata and R users: Note that I don’t use either, although I am familiar with both. All the R examples and exercises were provided by statistical consultant Kim Love and Stata examples and exercises by Jeff Meyer. Jeff and Kim will join us in the Q&A sessions and on the workshop website to answer your Stata and R questions.

Have additional questions? We’re here to help! Just email us at support@analysisfactor.com.