Tag: proc logistic

Propensity Score Estimation with PROC PSMATCH and PROC LOGISTIC

Do you wish you could predict the likelihood that one of your customers will open your marketing email? Or what if you could tell whether a new medical treatment for a patient will have a better outcome than the standard treatment? If you are familiar with propensity modeling, then you […]

Propensity Score Estimation with PROC PSMATCH and PROC LOGISTIC was published on SAS Users.

Example 9.14: confidence intervals for logistic regression models

Recently a student asked about the difference between confint() and confint.default() functions, both available in the MASS library to calculate confidence intervals from logistic regression models. The following example demonstrates that they yield d…

Example 9.14: confidence intervals for logistic regression models

Recently a student asked about the difference between confint() and confint.default() functions, both available in the MASS library to calculate confidence intervals from logistic regression models. The following example demonstrates that they yield d…

Example 9.14: confidence intervals for logistic regression models

Recently a student asked about the difference between confint() and confint.default() functions, both available in the MASS library to calculate confidence intervals from logistic regression models. The following example demonstrates that they yield d…

Some analysis on university ranking by US News

The yearly US News best college ranking is an important tool in comparing schools for students and their eager parents. The latest data is publicly available (paying 20 bucks would get full access) [Ref.1]. And the methodology is easy to find and expla…

Example 8.16: Exact logistic regression

In example 8.15, on Firth logistic regression, we mentioned alternative approaches to separation troubles. Here we demonstrate exact logistic regression. The code for this appears in the book (section 4.1.2) but we don’t show an example of it there. …

Example 8.15: Firth logistic regression

In logistic regression, when the outcome has low (or high) prevalence, or when there are several interacted categorical predictors, it can happen that for some combination of the predictors, all the observations have the same event status. A similar e…

Example 8.7: Hosmer and Lemeshow goodness-of-fit

The Hosmer and Lemeshow goodness of fit (GOF) test is a way to assess whether there is evidence for lack of fit in a logistic regression model. Simply put, the test compares the expected and observed number of events in bins defined by the predicted p…