search for: diets

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

...list, but if someone has time to answer I will be happy. I have tried to find out, but haven't found a consice answer. As an example I use "Pinheiro, J. C. & Bates, D. M. 2000. Mixed-effects models in S and S-PLUS. Springer, New York." page 225, where rats are fed by 3 different diets over time, which body mass has been measured. Response: Body mass, fixed effects Time*Diet, random effect ~Time|Rat. The main question is if the interaction term is significant (i.e. growth rate). My question is could I also look at the p-values of the main effects to say if body mass increase sign...

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

Suppose, we have 3 people called: Francis, Cedric and Nina. Base on what they have eaten, we want to cluster people by "diet", "non-diet". # original data file, named as filename "food.csv". Francis|potato Francis|chocolate Francis|chocolate Francis|milk Cedric|vegetable Cedric|vegetable Cedric|potato Nina|potato Nina|chocolate Nina|chocolate Nina|potato # Step 1: I

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 <-

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

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,

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

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

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",

...ion. The Time and Diet estimates are the same although the std-errors are different for Diet. --David. > > As an example I use "Pinheiro, J. C. & Bates, D. M. 2000. > Mixed-effects models in S and S-PLUS. Springer, New York." page 225, > where rats are fed by 3 different diets over time, which body mass has > been measured. Response: Body mass, fixed effects Time*Diet, random > effect ~Time|Rat. 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 m...

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,

On Apr 24, 2008, at 9:03 AM, Gabor Greif wrote: > > As you can see, the use-diet changes actually lower the build time > of kimwitu++! (this is as of yesterday's r50182). > Parity is not only reached, but surpassed. Thanks for these numbers. Do you know how much of this increase is due to co-allocating Use arrays with their users, and how much is due to the actual shrinking of

Hi all, in the last days I was busy gathering performance data about the "class Use"-related changes. I have nice measurements on a 8Gig MacPro with kimwitu++. This is important to say, because this machine is in plenty of memory, so swapping is not likely, which means that in more constrained setups (when swapping occurs) the use-diet approach is probably producing even better

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 ...

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