This reads as if you need to pick up a methods book on regression more generally. My guess is that "teaching method" is perfectly collinear with "TotalHours." Therefore, your model matrix is rank deficient. That is, if it is the case that teaching method=(1), (2), and (3) imply total hours=(0), (1), and (2), respectively, then, obviously, the effects of teaching and total hours are not discernable. R will automatically drop such collinear variables, which is most likely the reason for you getting NA results. Include either and you will get a (the same) result.
How to investigate if this is the reason: do table(teaching.method,TotalHours) If this outputs a diagonal matrix (a matrix with all zeros off the main diagonal), then the reason for the NAs is the perfect collinearity between teaching.method and TotalHours Further, you might want to include one of these variables as factors/dummies (or even factors coded as polynomial orthogonal contrasts), which is another reason to pick up a book on the topic. HTH, Daniel ------------------------- cuncta stricte discussurus ------------------------- -----Ursprüngliche Nachricht----- Von: r-help-boun...@r-project.org [mailto:r-help-boun...@r-project.org] Im Auftrag von SNN Gesendet: Wednesday, August 12, 2009 5:33 PM An: r-help@r-project.org Betreff: [R] logistic regression Hi All, I have data with 400 individuals and the following information Grade: pass or fail Sex: male or female Age Teaching.metho : can be 1,2,3 TotalHours: can be 0,1,2 I want to fit a logistic regression and for the TotalHours I am getting nothing! What could be the reason. What does the following message mean ? [Coefficients: (1 not defined because of singularities)] Below is my output Thanks for your help Call: glm(formula = Grade~ sex + age + teaching.method+ TotalHours, family = binomial, data = data) Deviance Residuals: Min 1Q Median 3Q Max -1.3844 -0.9686 -0.7688 1.2304 1.8871 Coefficients: (1 not defined because of singularities) Estimate Std. Error z value Pr(>|z|) (Intercept) -3.62178 1.20480 -3.006 0.00265 ** sex -0.32709 0.28539 -1.146 0.25175 age 0.04405 0.01371 3.213 0.00132 ** teaching.method 0.23878 0.20553 1.162 0.24533 TotalHours NA NA NA NA --- Signif. codes: 0 *** 0.001 ** 0.01 * 0.05 . 0.1 1 (Dispersion parameter for binomial family taken to be 1) Null deviance: 297.38 on 223 degrees of freedom Residual deviance: 282.93 on 220 degrees of freedom AIC: 290.93 -- View this message in context: http://www.nabble.com/logistic-regression-tp24943431p24943431.html Sent from the R help mailing list archive at Nabble.com. ______________________________________________ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code. ______________________________________________ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
