Ravi Varadhan
2013-Jan-30 16:01 UTC
[R] starting values in glm(..., family = binomial(link =log))
Try this: Age_log_model = glm(Arthrose ~ Alter, data=x, start=c(-1, 0), family=quasibinomial(link = log)) Ravi Ravi Varadhan, Ph.D. Assistant Professor The Center on Aging and Health Division of Geriatric Medicine & Gerontology Johns Hopkins University rvaradhan@jhmi.edu<mailto:rvaradhan@jhmi.edu> 410-502-2619 [[alternative HTML version deleted]]
Fischer, Felix
2013-Jan-30 16:18 UTC
[R] starting values in glm(..., family = binomial(link =log))
Thanks for your replies! It seems, that I can fit my model now, when I can provide the "right" starting values; however there remain warnings, such as: 1: In log(ifelse(y == 1, 1, (1 - y)/(1 - mu))) : NaNs wurden erzeugt 2: step size truncated due to divergence 3: step size truncated: out of bounds ... That makes me feel uncomfortable and I wonder whether I can "trust" the fitted model. Why is this kind of regression so picky about starting values compared to logistic regression? And is there a way to explain the difference between binomial - quasibinomial to a simple mind like mine? Best, Felix Von: Ravi Varadhan [mailto:ravi.varadhan@jhu.edu] Gesendet: Mittwoch, 30. Januar 2013 17:02 An: Fischer, Felix Cc: r-help@r-project.org Betreff: [R] starting values in glm(..., family = binomial(link =log)) Try this: Age_log_model = glm(Arthrose ~ Alter, data=x, start=c(-1, 0), family=quasibinomial(link = log)) Ravi Ravi Varadhan, Ph.D. Assistant Professor The Center on Aging and Health Division of Geriatric Medicine & Gerontology Johns Hopkins University rvaradhan@jhmi.edu<mailto:rvaradhan@jhmi.edu> 410-502-2619 [[alternative HTML version deleted]]