What is the most useful way to detect nonlinearity in logisticregression?
Dear Patrick, Component+residual plots can be defined for generalized linear models (including logistic regression) as for linear models, but they may require smoothing for interpretation. See, e.g., the cr.plots() functions in the car package, which works with glm objects. I hope this helps, John -------------------------------- John Fox Department of Sociology McMaster University Hamilton, Ontario Canada L8S 4M4 905-525-9140x23604 http://socserv.mcmaster.ca/jfox --------------------------------
-----Original Message----- From: r-help-bounces at stat.math.ethz.ch [mailto:r-help-bounces at stat.math.ethz.ch] On Behalf Of Patrick Foley Sent: Saturday, December 04, 2004 7:49 PM To: r-help at stat.math.ethz.ch Subject: [R] What is the most useful way to detect nonlinearity in logisticregression? It is easy to spot response nonlinearity in normal linear models using plot(something.lm). However plot(something.glm) produces artifactual peculiarities since the diagnostic residuals are constrained by the fact that y can only take values 0 or 1. What do R users find most useful in checking the linearity assumption of logistic regression (i.e. log-odds =a+bx)? Patrick Foley patfoley at csus.edu
______________________________________________ R-help at stat.math.ethz.ch mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide! http://www.R-project.org/posting-guide.html