search for: artifactu

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

My apriori apologies if this is felt to be the wrong list for this issue - although it starts with R, it's a combination of programs that creates the problem. Currently we are using windows metafile format for in-text tables for reports created in Word. However, we've discovered some artifactual lines being created in our final output once the Word document is changed to PDF. The process is as follows: # Simplest example code that contains all the sample features that create the problem library(lattice) test <- expand.grid(type = paste('Type', 1:4), success = c('Yes'...