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...t, such as: g3 <- gamm(y ~ xc +z+ s(int),family=binomial, weights=trial, random = list(Case=~1, z=~1),correlation=corAR1()) g4 <- gamm(y ~ xc +z+ s(int),family=binomial, weights=trial, random = list(Case=~1, z=~1, int=~1),correlation=corAR1()) Any help would be appreciated. Thanks. Will Shadish ******************************************** g1 $lme Linear mixed-effects model fit by maximum likelihood Data: data Log-likelihood: -437.696 Fixed: fixed X(Intercept) Xz Xint Xs(xc)Fx1 0.6738466 -2.5688317 0.0137415 -0.1801294 Random effects: Formula: ~X...

...for, but adding the nonlinearity modeling of GAM. Is either of these formulations giving me what I want--a test of whether trend differs significantly over cases or not. Thanks for any help you can offer. I have worked very hard to solve this on my own, and just can't seem to do so. Will Shadish > PCP PID SessIDX DVY TX 1 1 1 4 0 2 1 2 5 0 3 1 3 5 0 4 1 4 8 0 5 1 5 3 1 6 1 6 0 1 7 1 7 0 1 8 1 8 0 1 9 1 9 0 1 10 2 1 2 0 11 2 2 2 0 12 2 3 4 0 1...

...ways indicate the polynomial exponent directly? We ask because Hothorn and Everitt said "Roughly, the complexity of a cubic spline is about the same as a polynomial of degree one less than the degrees of freedom." Sorry we attributed the latter to you, by the way. Will -- William R. Shadish Distinguished Professor Founding Faculty Chair, Psychological Sciences Mailing Address: William R. Shadish University of California School of Social Sciences, Humanities and Arts 5200 North Lake Rd Merced CA 95343 Physical/Delivery Address: University of California Merced ATTN: William Shadish S...

Dear R users, I have seven regression lines I´d like to compare, in order to find out if these are significatively different. The main problem is that these are curves, non normal, non homogeneous data, I´ve tried to linearize them but it has not worked. So I´d like to know if you know any command or source in R which explains how to perform this kind of comparison. Thanks in advance for your

...lt of rounding error in the computation of the df difference and deviance difference, and that we should treat this as indicating the models are not different from each other. Has anyone experienced this before? Is our interpretation reasonable? Thanks to anyone who is able to offer advice. Will Shadish -- View this message in context: http://r.789695.n4.nabble.com/GAM-Chi-Square-Difference-Test-tp4636523.html Sent from the R help mailing list archive at Nabble.com.