search for: gluc

Displaying 4 results from an estimated 4 matches for "gluc".

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2007 Nov 14
2
Help with Bartlett's test on linear model
...nd I cannot find any examples on the internet. There are some examples for comparisons of variances but not linear models. If I take the hellung data set, which is the example in Dalgaard's book. I know var.test works fine but I want to learn how to use the Bartlett's test. > hellung$glucose <- factor(hellung$glucose, labels=c("Yes","No")) > attach(hellung) > tethym.gluc <- hellung[glucose=="Yes",] > tethym.nogluc <- hellung[glucose=="No",] > lm.nogluc <- lm(log10(diameter)~log10(conc), data=tethym.nogluc) > lm....
2007 Nov 22
3
anova planned comparisons/contrasts
..., I'm trying to figure out how anova works in R by translating the examples in Sokal And Rohlf's (1995 3rd edition) Biometry. I've hit a snag with planned comparisons, their box 9.4 and section 9.6. It's a basic anova design: treatment <- factor(rep(c("control", "glucose", "fructose", "gluc+fruct", "sucrose"), each = 10)) length <- c(75, 67, 70, 75, 65, 71, 67, 67, 76, 68, 57, 58, 60, 59, 62, 60, 60, 57, 59, 61, 58, 61, 56, 58, 57, 56, 61, 60, 57, 58, 58, 59, 58, 61, 5...
2013 Nov 07
2
Error running MuMIn dredge function using glmer models
...t I am getting an error message that I cannot decode. This error only occurs when I use glmer. When I use an lmer analysis on a different response variable every works great. Example using a simplified glmer model global model: mod<- glmer(cbind(st$X2.REP.LIVE, st$X2.REP.DEAD) ~ DOMESTICATION*GLUC + (1|PAIR), data=st, na.action=na.omit , family=binomial) The response variables are the number of survival and dead insects (successes and failures) DOMESTICATION is a 2 level factor. GLUC is a continuous variable. PAIR is coded as a factor or character (both ways fail). This model functions co...
2011 Feb 08
3
intervals {nlme} lower CI greater than upper CI !!!????
Hi folks... check this out.. > GLU<-lme(gluc~rt*cd4+sex+age+rf+nadir+pharmac+factor(hcv)+factor(hbs)+ + haartd+hivdur+factor(arv), + random= ~rt|id, na.action=na.omit) > intervals(GLU)$fixed lower est. upper (Intercept) 67.3467070345 7.362307e+01 7.989944e+01 rt *0.0148050160*...