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Master Binary Logistic Regression

Overview:

Learn what Binary Logistic Regression Is, When and How to Implement it, and Most Importantly, How to Understand the Results

Sooner or later, you will need to answer a research question by creating a model with a categorical dependent variable.

And no matter how many ways you transform the data, you just can't force it into a linear regression or ANOVA.

But luckily, there is logistic regression, which is just a hop, skip, and a jump away from linear regression. Although logistic regression does contain a few more complexities and new statistical concepts, it is within reach of anyone who can use linear models.

This workshop will guide you through those new concepts. You will learn the similarities and differences between linear and logistic regression, and how to implement, work with, and understand the differences.

 
What You Will Learn:

 

After attending the workshop, you will be able to:

  • Understand why linear regression does not work for categorical data, and why logistic regression does

  • Decide whether logistic regression is appropriate for your data

  • Interpret results from a logistic regression analysis

  • Know the difference between probability, odds, and odds ratios, and convert from one to another

  • Interpret odds ratios for categorical and continuous predictor variables

  • Test which logistic regression model best fits the data

  • Check whether the assumptions are being met

  • Deal with data issues unique to categorical models

  • Understand the terminology used in software manuals so that you can choose the appropriate options for a particular analysis.

In short, after taking this workshop, you will be able to recognize the need for, implement, test, and interpret a binary logistic regression model.
Format:
Webinar live online workshop

Webinars are a fabulous way to learn. You get all the advantages of a live workshop without the disadvantages.

I will be conducting the workshop live. You attend over the internet as you see what is happening on my computer screen. Audio is through either your computer speakers/microphone or by telephone. Webinars are highly interactive--see the presentation on my screen, ask questions out loud or write it into the chat--yet you never have to leave your house or office. 

Save on travel expenses and fit it into your regular schedule. And because you’re not travelling, we don’t have to concentrate an overwhelming amount of information into marathon session. We can spread it out in digestible amounts.

And best of all, unlike live workshops, the presentations will be recorded. You will get the audio and video recording from every session, so if you miss one, or need to review the material in a few months, you’ll have it forever.
Who Is It For:
This workshop is for you if you:
  • Have tried to do a binary logistic regression before, but found it confusing or difficult, and don't really understand it.
  • Have used linear regression or ANOVA, and want to expand your knowledge.
  • Know you will soon need to implement a logistic regression
  • Want to expand your statistical capacity.

Prerequisites:

  • You will get the most out of the workshop if you have had at least two statistics classes, and some experience in data analysis, particularly linear modeling.
  • You need to be familiar with using a statistical software package. I will present examples and provide data sets and code for both SPSS and SAS. I am familiar with S-Plus, Stata, Minitab, and JMP, and all are reasonable options for implementing logistic regression. This workshop focuses on the concepts, meanings, and options--it is not about the software. That said, I will do my best to answer software questions, but I'm not familiar with the intricacies of defaults in these other packages.
What's Included:
  • 4 - 90 minute live webinar workshop sessions.  Each session will contain a presentation and time for questions.  You will hear me and see exactly what is happening on my screen.

  • A 60 minute Q&A session. Just your questions and my answers. This is two weeks later, so you have a chance to try things out on your own data, then come back with questions. It's when you use these techniques on your own data that you cement your learning.

  • PDF handouts of the presentations, which will be available ahead of each session, on which you can take notes.

  • Data files and SAS and SPSS code to run, explore, and practice all of the examples yourself.

  • Video Recordings of each workshop session made available within 48 hours.

  • Access to our central Workshop Basecamp. This is a web-based location where you can post questions, get call-in information for each webinar session, and download handouts and recordings.

  • Participants are encouraged to ask questions about implementing these techniques in their own analyses in addition to general questions about the topic.  (But please keep questions to the topic of the workshop so that they’re useful for everyone). 

  • Exercises.  (Yes, homework!).  It’s optional, but you’ll get more out of the workshop if you participate fully by doing the exercises.  You can use one of the data sets provided, or your own.
Registration Fee:

This workshop has ended. If you'd like a notice when the home-study version is ready, please fill in your name and email address below.

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Extras

1. The first 10 people who register will get an additional 60-minute Q&A sessions 4 weeks after the workshop ends. Try out what you learned, then call in with your questions.

2. Consultations with Karen Grace-Martin within the weeks that the workshop runs (and for two weeks after) are 20% off my regular rates for workshop participants.
Refund Policy

Your registration fee is fully refundable up to 72 hours in advance minus a $25 administration fee. Because enrollment is limited, no refunds will be granted after the program begins.

That said, your satisfaction is guaranteed. If you participate in the full workshop and find you are not satisfied for any reason, we will give you a full refund. Just notify us within 90 days of the conclusion of the program.