similar to: Main effects and interactions in mixed linear models

HI Dave, My comment was based? on: " >The main question with this test was if the interaction term is significant (i.e. growth rate). However, my question is could I also look at the p-values of the main effects to ?>say if body mass increase significant with body mass?" Here, the result shown were from the summary of the linear model.?? We report the p-values of the main

Dear Dr. Bates, and R-help, I've tried the anova function to test the difference between two coefficients, as shown on page 225 of your book "Mixed Effects Models in S and S-Plus (Statistics and Computing)". When I type: anova( fm2BW.lme, L = c(TimeDiet2 = 1, TimeDiet3 = -1) ) I got the following error message: Error: unexpected '=' in "anova( fm2BW.lme, L =

Hi, I'm having difficulty with getting a table to show with multiple rows and columns. Below is the commands that I've typed in and errors that I am getting. Thank you. Laura Table trying to enter: Diet: Binger-yes: Binger-No: Total: None 24 134 158 Healthy 9 52 61 Unhealthy 23 72 95 Dangerous 12 15 27 >

Otras variantes con y sin paquetes adicionales... > sapply(split(datIn$Gain, as.factor(datIn$Diet)), mean) d1 d2 d3 280 278 312 > by(datIn$Gain, datIn$Diet, mean) datIn$Diet: d1 [1] 280 -------------------------------------------------------------- datIn$Diet: d2 [1] 278 -------------------------------------------------------------- datIn$Diet: d3 [1] 312 > > library(dplyr) >

Me gusta la respuesta uqe has dado, pero si por ejemplo, alguno de los datos tiene datos faltantes, entonces devuelve NA. He probado con: sapply(split(datos$uno, as.factor(datos$dos)), mean(na.rm=TRUE)) pero da fallo. ¿Cómo se podría hacer para que devolviera además la media obviando los NA y que contara el numero de NA por categoria? > Date: Wed, 28 Oct 2015 00:13:45 +0100 > From: cof

Estimados Cuando existia epicalc, había una manera muy fácil de determinar la media de una variable (en esta caso Gain) por grupos, en este caso (Diet). ?Como se puede hacer ahora? Diet Gain 1 d1 270 2 d1 300 3 d1 280 4 d1 280 5 d1 270 6 d2 290 7 d2 250 8 d2 280 9 d2 290 10 d2 280 11 d3 290 12 d3 340 13 d3 330 14 d3 300 15 d3 300

Hello This is Elaine. I am using package lattice to generate boxplots. Using Richard's code, the display was almost perfect except the outlier shape. Based on the following code, the outliers are vertical lines. However, I want the outliers to be empty circles. Please kindly help how to modify the code to change the outlier shapes. Thank you. code package (lattice) dataN <-

Hi, In the examples from the ReShape package there is a simple example of using melt followed by cast that produces a smallish amount of output about the chicks database. Here's the code: library(reshape) names(ChickWeight) <- tolower(names(ChickWeight)) chick_m <- melt(ChickWeight, id=2:4, na.rm=TRUE) DietResults <- cast(chick_m, diet + chick ~ time) DietResults My challenge

Hi all , I have a dataframe (Hypertension) with following headers :- > Hypertension ID Hypertension(before drug A) Hypertension(On drug A) On drug B? Healthy diet? 1 160 90 True True 2 190

Hello I ran the code below but it said: no object "'panel.xyplot.intermediate.hh'" Please kindly advise how to modify the code. thank you. (It works with panel.bwplot.intermediate.hh) Elaine code library(HH) # data input dataN <-read.csv("H:/R_data/Mig_bird_586.csv",header=T, row.names=1) dim(dataN) dataN[1,] str(dataN) diet.code <-

Hello I want to draw a xyplot. Its dots will have three colors: red for meat, green for vegetable, and blue for both. I used the code below but could not make the dot in the same group show the same color. Please kindly advise how to modify it. Thank you. code library (lattice) diet.code <- c("Herbivore", "Omnivore", "Carnivore") Diet.colors <-

according to the documentation of the cast function in the reshape function, I would expect this bit of code from the examples to calculate marginal means over only the 'diet' variable. #Chick weight example names(ChickWeight) <- tolower(names(ChickWeight)) chick_m <- melt(ChickWeight, id=2:4, na.rm=TRUE) cast(chick_m, diet + chick ~ time, mean, margins="diet") But,

I am running the following code on the coagulation data and I am getting an error. Please let me know if I am missing anything from my code. coag<- matrix( scan("//Samba3/nair/R/blood.dat", sep=","), 24, 3, byrow=TRUE) colnames(coag) <- c("time","diet","order") coag <- as.data.frame(coag) oneway.test(time ~ diet, data=coag,

I am trying to apply a permuation-based MANOVA (Anderson 2001) to a set of morphological data from three ecomorphs of fish reared under two different conditions and measured at two points during ontogeny. I will supply a distance matrix based on Procrustes distances calculated outside of vegan. I have not found an example of a design such as this for adonis. However, I have designed my factors

I have a simple dataset of a numerical dependent Y, a numerical independent X and a categorial variable Z with three levels. I want to do linear regression Y~X for each level of Z. How can I do this in a single command that is without using lm() applied three isolated times? -- View this message in context: http://r.789695.n4.nabble.com/Linear-regression-on-several-groups-tp2322835p2322835.html

Hi everyone, I'm having trouble adding error bars to a grouped barchart in lattice. I know that this topic has been addressed quite a bit, as I've been searching the internet for a while to try to troubleshoot the issue, but I've not been able to find any solution that I could get working on my data. I was wondering if someone could look at my code and tell me what I'm doing

I'm trying to use R for some of the analysis shown in Box, Hunter and Hunter (1979, I believe) using the aov function. I'm using the first example in chapter 6, where they are determining the analysis of varience between 4 treatments. In this example, the are determineing the analysis between and within treatments, which I can get by aov(response~treatment+Error(treatment)) Where

In /usr/share/doc/rsync/README.gz: BUG REPORTS ----------- If you have web access then please look at... Well what if you don't have web access? You don't mention what to do then. "Send bugs to rsync@lists.samba.org" probably. OK. Will do. Here's one now: $ rsync -avz debian.linux.org.tw:var/lib/apt/diet.lists var/lib/apt/diet.lists receiving file list ...

Dear users, I think my questions are pretty simple, but I got lost in the hundreds of par() and plot() arguments and plot functions, so I don't know in which direction I should go. Here is my sample dataset: test <- structure(list(DIET = structure(c(1L, 1L, 1L, 1L, 1L, 3L, 3L, 3L, 3L, 3L, 2L, 2L, 2L, 2L, 2L, 4L, 4L, 4L, 4L, 4L), .Label = c("G", "GG", "L",

An excerpt from dataset ChickWeight: ??? weight Time Chick Diet 1?????? 42??? 0???? 1??? 1 2?????? 51??? 2???? 1??? 1 3?????? 59??? 4???? 1??? 1 I am interested in the residuals of the dataset.? Specifically in saving them to another format. I have been creating text files with sink. CW.lm <- lm(weight ~ Diet, ChickWeight) resid.CW.lm <- resid(CW.lm) But when I call: resid.CW.lm The data