
My Most Used Reference
Applied Logistic
Regression
More Books — My Library 
Recent Comments
 Raymondo on What are ZValues in Logistic Regression?
 Matthew on What is (Multivariate) Logistic Regression?
 Logistic Regression Sigmoid Function – Wang Zhe on How to Solve the Logistic Regression Equation for the Probability p.
 Martin Cohen on Understanding Logistic Regression Output:
Background Part 1 – Least Squares Regression  Martin Cohen on Understanding Logistic Regression Output:
Background Part 1 – Least Squares Regression

Recent Posts
 What are ZValues in Logistic Regression?
 How Big a Sample? How Many XVariables?

Understanding Logistic Regression Coefficient Output:
Part 5 — Assessing Uncertainty 
Understanding Logistic Regression Coefficient Output:
Part 4 — Making Predictions  How to Solve the Logistic Regression Equation for the Probability p.
Archives
Categories
Meta
Tag Archives: logistic regression
Logistic Regression Odds Ratio — The Math
In this article, I am going to show you why the odds ratio for an variable in a logistic regression is simply the exponential of the regression coefficient. This article just contains “the math” and no interpretation. A discussion of … Continue reading
Understanding Logistic Regression Output:
Part 3 — Assessing the Effects of the XVariables
In logistic regression, as in leastsquares regression, you often want to try to assess the effects of the independent variables on the dependent variable. In logistic regression, however, things are somewhat more complicated than in leastsquares regression as I explain … Continue reading
What is the Odds Ratio in Logistic Regression?
Most logistic regression software outputs (or can be asked to output) odds ratios along with the regression coefficients. These odds ratios are the exponential of the corresponding regression coefficient: For example, if the logistic regression coefficient is the … Continue reading
Understanding Logistic Regression Output:
Part 2 — Which Variables Matter
This article discusses one of the most important uses of the coefficient table, determining which variables matter. It is the second part of a fivepart series discussing the logistic regression output coefficient table and its uses. Click here to see … Continue reading
What is the (Multivariate) Logistic Regression Equation?
In logistic regression, the log odds is modeled as a linear functions of the variables. Thus, the logistic regression equation is: Once the logistic regression has been “run,” the software will calculate estimates for , , , … … Continue reading
Understanding Logistic Regression Output:
Background Part 1 – Least Squares Regression
As I have indicated previously on this web site, I am going to use regular linear leastsquares regression as a starting point for explaining logistic regression. Thus, I will be assuming that you have some familiarity with regular linear regression. … Continue reading
About Odds and Odds Ratios
From Odds to Probability Related Articles: The Odds Ratio in Logistic Regression The Effects of the XVariables in Logistic Regression We have all used the word “odds” to describe the probability of something. “Odds are it will rain tomorrow” means … Continue reading
A Little About Logs
For some reason, which remains mysterious to me, all throughout high school math classes and the first year college math classes (at least in the U.S.), the natural logarithm (the log to the base e) is usually referred to as … Continue reading
What a Multivariate Logistic Regression Data Set Looks Like: An Example
Just to be sure that you have a clear idea of what a data set that is appropriate for logistic regression analysis looks like, I am providing an example in this article. As I indicated in the previous article, a … Continue reading
Posted in Basic
Tagged data mining, logistic regression, multivariate logistic regression
24 Comments
What is (Multivariate) Logistic Regression?
Note: If you want to jump directly to the “punch line” skipping all of my explanation and development (and making me feel unappreciated :() click here. Recall that in regular least squares regression we fit a line to the data. … Continue reading