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Logistic Regression

Blog posts and articles about the statistical method called Logistic Regression and its use in quality improvement projects.

Businesses are getting more and more data from existing and potential customers: whenever we click on a web site, for example, it can be recorded in the vendor's database. And whenever we use electronic ID cards to access public transportation or other services, our movements across the city may be analyzed. In the very near future, connected objects such as cars and electrical appliances will... Continue Reading
By looking at the data we have about 500 cardiac patients, we've learned that easy access to the hospital and good transportation are key factors influencing participation in a rehabilitation program. Past data shows that each month, about 15 of the patients discharged after cardiac surgery do not have a car. Providing transportation to the hospital might make these patients more likely to join... Continue Reading

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In part 2 of this series, we used graphs and tables to see how individual factors affected rates of patient participation in a cardiac rehabilitation program. This initial look at the data indicated that ease of access to the hospital was a very important contributor to patient participation. Given this revelation, a bus or shuttle service for people who do not have cars might be a good way to... Continue Reading
Suppose you’ve collected data on cycle time, revenue, the dimension of a manufactured part, or some other metric that’s important to you, and you want to see what other variables may be related to it. Now what? When I graduated from college with my first statistics degree, my diploma was bona fide proof that I'd endured hours and hours of classroom lectures on various statistical topics, including l... Continue Reading
My previous post covered the initial phases of a project to attract and retain more patients in a cardiac rehabilitation program, as described in a 2011 Quality Engineering article. A Pareto chart of the reasons enrolled patients left the program indicated that the hospital could do little to encourage participants to attend a greater number of sessions, so the team focused on increasing initial... Continue Reading
Over the past year I've been able to work with and learn from practitioners and experts who are using data analysis and Six Sigma to improve the quality of healthcare, both in terms of operational efficiency and better patient outcomes. I've been struck by how frequently a very basic analysis can lead to remarkable improvements, but some insights cannot be attained without conducting more... Continue Reading
When running a binary logistic regression and many other analyses in Minitab, we estimate parameters for a specified model based on the sample data that has been collected. Most of the time, we use what is called Maximum Likelihood Estimation. However, based on specifics within your data, sometimes these estimation methods fail. What happens then? Specifically, during binary logistic regression, an... Continue Reading
With Speaker John Boehner resigning, Kevin McCarthy quitting before the vote for him to be Speaker, and a possible government shutdown in the works, the Freedom Caucus has certainly been in the news frequently! Depending on your political bent, the Freedom Caucus has caused quite a disruption for either good or bad.  Who are these politicians? The Freedom Caucus is a group of approximately 40... Continue Reading
Imagine a multi-million dollar company that released a product without knowing the probability that it will fail after a certain amount of time. “We offer a 2 year warranty, but we have no idea what percentage of our products fail before 2 years.” Crazy, right? Anybody who wanted to ensure the quality of their product would perform a statistical analysis to look at the reliability and survival of... Continue Reading
If you want to use data to predict the impact of different variables, whether it's for business or some personal interest, you need to create a model based on the best information you have at your disposal. In this post and subsequent posts throughout the football season, I'm going to share how I've been developing and applying a model for predicting the outcomes of 4th down decisions in Big... Continue Reading
The NCAA Tournament is right around the corner, and you know what that means: It’s time to start thinking about how you’re going to fill out your bracket! For the last two years I’ve used the Sagarin Predictor Ratings to predict the tournament. However, there is a problem with that strategy this year. The old method uses a regression model that calculates the probability one team has of beating... Continue Reading
by Lion "Ari" Ondiappan Arivazhagan, guest blogger.  An alarming number of borewell accidents, especially involving little children, have occurred across India in the recent past. This is the second of a series of articles on Borewell accidents in India. In the first installment of the series, I used the G-chart in Minitab Statistical Software to predict the probabilities of innocent children... Continue Reading
If you wanted to figure out the probability that your favorite football team will win their next game, how would you do it?  My colleague Eduardo Santiago and I recently looked at this question, and in this post we'll share how we approached the solution. Let’s start by breaking down this problem: There are only two possible outcomes: your favorite team wins, or they lose. Ties are a possibility,... Continue Reading
Recently, Minitab’s Joel Smith posted about his vacation and being pooped on twice by birds. Then guest blogger Matthew Barsalou wrote a wonderful follow-up on the chances of Joel being pooped on a third time. While I cannot comment on how Joel has handled this situation psychologically so far, I can say that if I had been pooped on twice in a short amount of time, I would be wary of our... Continue Reading
In my recent meetings with people from various companies in the service industries, I realized that one of the problems they face is that they were collecting large amounts of "qualitative" data: types of product, customer profiles, different subsidiaries, several customer requirements, etc. As I discussed in my previous post, one way to look at qualitative data is to use different types of... Continue Reading
In his post yesterday, my colleague Jim Colton applied binary logistic regression to data on the current ebola virus outbreak in Guinea, Liberia, and Sierra Leone, and revealed that, horrific as it is, this outbreak actually appears to have a lower death rate than some earlier ones.  He didn't address the potential for a global ebola pandemic, but over the last few days more than enough leading... Continue Reading
The current Ebola outbreak in Guinea, Liberia, and Sierra Leone is making headlines around the world, and rightfully so: it's a frightening disease, and last week the World Health Organization reported its spread is outpacing their response. Nearly 900 of  the more than 1,600 people infected during this outbreak have died, including some leading medical professionals trying to stanch the... Continue Reading
If betting wasn't allowed on horse racing, the Kentucky Derby would likely be a little-known event of interest only to a small group of horse racing enthusiasts. But like the Tour de France, the World Cup, and the Masters Tournament, even those with little or no knowledge of the sport in general seem drawn to the excitement over its premier event—the mint juleps, the hats...and of course,... Continue Reading
In April 2012, I wrote a short paper on binary logistic regression to analyze wine tasting data. At that time, François Hollande was about to get elected as French president and in the U.S., Mitt Romney was winning the Republican primaries. That seems like a long time ago… Now, in 2014, Minitab 17 Statistical Softwarehas just been released. Had Minitab 17, been available in 2012, would have I... Continue Reading