similar to: Guidance for reporting results from lme test?

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I want to use the plot(model) function to generate Tukey-anscomb and Q-Q plots of a lm(). I manage to change all labels but the main one which apparently is neither main or sub. So far I have tried as par setting: cex (changes symbol size within the plot), cex.main (no effect), cex.sub (no effect) cex.lab (changes label size), cex.axis (changes axis label size). What I would like to change is the

Hello everybody 1. If there is/ever will be a function to perform "duncan multiple range test" please inform me at once. 2. Is there a way to create a grouping as duncan does from TukeyHSD output? My experimental design contained 62 genotypes, so the pairwise comparison is not that usefull and clear to look at. How would I do that? Is there an other test that does give grouping as

I don't think, this has been answered: > I'm trying to run a 3-way within-subject anova in lme with 3 > fixed factors (Trust, Sex, and Freq), but get stuck with handling > the random effects. As I want to include all the possible random > effects in the model, it would be something more or less > equivalent to using aov > > > fit.aov <- aov(Beta ~ >

I am trying to run a GLMM on some binomial data. My fixed factors include 2 dichotomous variables, day, and distance. When I run the model: modelA<-glmmPQL(Leaving~Trial*Day*Dist,random=~1|Indiv,family="binomial") I get the error: iteration 1 Error in MEEM(object, conLin, control$niterEM) : Singularity in backsolve at level 0, block 1 >From looking at previous help

Dear All, I wonder if anyone can please offer any advice on a model including 2 fixed effects and 1 random effect, as well as a covariate? The experimental design is as follows: I have a two by two factor design, where the two factors, Age (A) and Group size (G), both have 2 levels (old or young, and 1 or 3 respectively), and I am interested in the effect of these factors upon a continuous

Dear R-Helpers, I would like to know what syntax I need to use to do a nested anova for 1. a continuous variable and 2. count data (x out of y) 1. The first I used to do in SPSS and I would like to be able to do it in R as well. This is the hierarchical model I would like to use: a continuous variable explained by factor A(fixed) + factor B(random) nested in A + factor C (random) nested in

list, i am using lmer to fit multilevel models and trying to use anova to compare the models. however, whenever i run the anova, the AIC, BIC and loglik are different from the original model output- as below. can someone help me out with why this is happening? (i'm hoping the output assocaited with the anova is right!). thank you, darren > unconditional<-lmer(log50 ~ 1 + (1 |

I' ve seen that several people are looking for a function that creates a barplot with an error indicators (I was one of them myself). Maybe you will find the following code helpful (There are some examples how to use it at the end): # Creates a barplot. #bar.plot() needs a datavector for the height of bars and a error #indicator for the interval #many of the usual R parameters can be set:

Hi guys, I'm a photographer and I want to use the software that my camera manufacturer makes. I can install the application like View NX 2 but Nikon trasnfer makes an error. I want to know what information do I have to gather for help or what should I need to correct this erros. If any interested of helping please just reply. Thank you.

Buenos dias a todos, Me gustaria genear n muestras de una N(0,1) a determinados intervalos de tiempo. Asi por ejemplo, si el vector de tiempos es tiempos <- c(2, 4, 6) la primera columan debe generarse a los 2 segundos de ejecutado el script, la 2a columna a los 4 segundos y la ultima a los 6 segundos. Al final el tiempo total de ejecucion sera aproximadamente 12 segundos para completar