Logistic regression

My Favorite Graphs

December 5, 2011 | Nina Zumel

The important criterion for a graph is not simply how fast we can see a result; rather it is whether through the use of the graph we can see something that would have been harder to see otherwise or that could not have been seen at all. – William Cleveland, The ... [Read more...]

Learn Logistic Regression (and beyond)

November 23, 2010 | John Mount

One of the current best tools in the machine learning toolbox is the 1930s statistical technique called logistic regression. We explain how to add professional quality logistic regression to your analytic repertoire and describe a bit beyond that. A statistical analyst working on data tends to deliberately start simple move ... [Read more...]

Example 8.15: Firth logistic regression

November 22, 2010 | Ken Kleinman

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...
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Example 8.8: more Hosmer and Lemeshow

October 5, 2010 | Ken Kleinman

This is a special R-only entry.In Example 8.7, we showed the Hosmer and Lemeshow goodness-of-fit test. Today we demonstrate more advanced computational approaches for the test.If you write a function for your own use, it hardly matters what it looks l...
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R Commander – logistic regression

June 23, 2010 | Ralph

We can use the R Commander GUI to fit logistic regression models with one or more explanatory variables. There are also facilities to plot data and consider model diagnostics. The same series of menus as for linear models are used to fit a logistic regression model. Fast Tube by Casper ... [Read more...]

Confusing slice sampler

May 18, 2010 | xi'an

Most embarrassingly, Liaosa Xu from Virginia Tech sent the following email almost a month ago and I forgot to reply: I have a question regarding your example 7.11 in your book Introducing Monte Carlo Methods with R.  To further decompose the uniform simulation by sampling a and b step by step, ...
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