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...,xlab="",ylab="Offspring number", aspect="fill",scales=list(x=list(draw=F)),strip=T) By the way, since there is no x-axis, I just want to control space parameters in y-axis. Does someone have any idea to fulfil this aim? Thank you very much for kind help! Best regards, Jianghua -- View this message in context: http://n4.nabble.com/How-to-control-spaces-between-axis-tick-and-label-in-xyplot-or-xYplot-tp1010689p1010689.html Sent from the R help mailing list archive at Nabble.com.

...byear) Model 2: sum_surv15 ~ s(FLBS) + SES + s(byear) + s(FLBS, byear) Resid. Df Resid. Dev Df Deviance F Pr(>F) 1 1202.21094 601.27 2 1201.43848 601.29 0.77246 -0.02 #################################################### Thank you very much! Jianghua Liu, University of Sheffield -- View this message in context: http://www.nabble.com/Why-there-is-no-p-value-from-likelihood-ratio-test-using-anova-in-GAM-model-fitting--tp23275224p23275224.html Sent from the R help mailing list archive at Nabble.com. [[alternative HTML version deleted]]

.... Thus, there is only one y-axis in the left. However, number of offspring displayed is in integer. How to display such numbers in decimal numbers, e.g. decimal number with one digit after decimal point? Does someone have any idea to fulfil this aim? Thank you very much for kind help! Best regards, Jianghua -- View this message in context: http://n4.nabble.com/How-to-control-number-of-significant-digits-figures-in-y-axis-tp1010693p1010693.html Sent from the R help mailing list archive at Nabble.com.

Dear all, I am trying to calculate some measure of the amount of variability in the response variable that is explained by a model fitted in lmer m1<-lmer(response-var ~ Condition+(1|Site/Area/Transect),family="binomial") . I've seen from the literature that the precentage of explained deviance is a common measure. How can I calculate it? Thanks a lot for your help, I hope this

...ctor)) , where vector is the (1,cafr,I(cafr^2)) which representing empirical data vector at considered point. If this is correct, I think I can use this method to draw standard error line. Otherwise, would you please suggest a reasonable one? Thank you very much for your attention! Yours sincerely, Jianghua -- View this message in context: http://old.nabble.com/standard-error-for-the-estimated-value-%28lmer-fitted-model%29-tp26414507p26414507.html Sent from the R help mailing list archive at Nabble.com. [[alternative HTML version deleted]]

Dear R users, I have a problem in plotting 3 dimensional graph using mixed models. My model is sur_prop ~ afr_c+I(afr_c^2)+I(afr_c^3)+byear_c+I(byear_c^2)+I(byear_c^3)+I(byear_c^4)+(1|Studyparish)+afr_c:byear_c +afr_c:I(byear_c^2)+afr_c:I(byear_c^3)+afr_c:I(byear_c^4)+I(afr_c^2):byear_c+I(afr_c^2):I(byear_c^2)+I(afr_c^2):I(byear_c^3)+I(afr_c^2):I(byear_c^4) This is a study on the effect of

I am a little bit confusing about the following help message on how to fit a GAM model with interaction between factor and smooth terms from http://rss.acs.unt.edu/Rdoc/library/mgcv/html/gam.models.html: ?Sometimes models of the form: E(y)=b0+f(x)z need to be estimated (where f is a smooth function, as usual.) The appropriate formula is: y~z+s(x,by=z) - the by argument ensures that the smooth

Dear R users, I have a problem with multicollinearity in mixed models and I am using lmer in package lme4. From previous mailing list, I learn of a reply "http://www.mail-archive.com/r-help at stat.math.ethz.ch/msg38537.html" which states that if not for interpretation but just for prediction, multicollinearity does not matter much. However, I am using mixed model to interpret something,