search for: fertility

Sorry for bothering you - but I have a little problem. I`m completely new in R and trying to use lmer. That works, but I m not sure if my code is right, so I would just like to get an opinion from the experts. I have a Growthrate of plants (RGR Fixed Factors: Fertilizer, Status (alien or native plants) and their interaction Random Factors: Age is a covariable; than I have plantfamily and

Hi, I have this: lme(y~x1+x2,random=~1|x1/x2) How to make this random effect using lmer? I try this: lmer(y~x1+x2+(1|x1/x2) But it dont work. Any idea? Thanks Ronaldo -- System halted! -- |> // | \\ [***********************************] | ( ?? ?? ) [Ronaldo Reis J??nior ] |> V [UFV/DBA-Entomologia ] | / \ [36570-000 Vi??osa -

Dear R Community, Below is a problem with a simple ggplot2 graph. The code returns the error message below. Error: stat_count() must not be used with a y aesthetic. My code is below and the data is attached as a ?text? file. # Graph of the probabilities library(digest) library(DT) datatable(probability) str(probability) probability$Fertilizer <- as.factor(probability$Fertilizer)

Hi! How to calculate the correct SE of mean in a nested or spliplot anova? Nested example: --------------------- m <- aov(Glycogen~Treatment+Error(Treatment/Rat/Liver)) > m Call: aov(formula = Glycogen ~ Treatment + Error(Treatment/Rat/Liver)) Grand Mean: 142.2222 Stratum 1: Treatment Terms: Treatment Sum of Squares 1557.556 Deg. of Freedom 2 Estimated

Hello R-help, I'm studying an example in the R book.? The data file is available from the link below.http://www.bio.ic.ac.uk/research/mjcraw/therbook/data/fertilizer.txt Could you explain Why the results from lme() and lmer() are different in the following case? In other examples, I can get the same results using the two functions, but not here...? Thank you.Miya library(lme4)library(nlme)#

...skip the tedious process of collecting information to assemble a table, but I am not sure if the function I want already exists. Any suggestion would be appreciated. I have a working example, as required by the posting guide: my_swiss = swiss[-1,] my_swiss$facto = rep(1:2,nrow(my_swiss)/2) t.test(Fertility~facto,data=my_swiss) by(my_swiss$Fertility,my_swiss$facto, sd) t.test(Agriculture~facto,data=my_swiss) by(my_swiss$Agriculture,my_swiss$facto, sd) ttable <- function(formula, data) { ???? } ttable(Fertility + Agriculture ~ facto, data=my_swiss) facto ? ? ? ? ? ? ?1 ? ? ? ? ? ? ? ? ? ? ? ? ?2...

Hello. My name is Ana. I?m doing an eology master, and I?m just learning how R works. I have a Mac OS X 10.5.6, and I?m tryng to run just a simple ANOVA nanalyses. I dowloaded R version 2.10.0, and it seems I have problems with the script. I don?t know what to do, I?ve already change the languages, be sure of being working in the correct directory and doesn?t work the script is: #1. example

Hi James, If you want to specify the y-values, you need to use stat="identity" as below: ggplot(probability, aes(x=Fertilizer, y=prob)) + geom_bar(stat="identity", aes(fill=Treatment)) best, huzefa On Tue, Apr 12, 2016 at 1:02 PM, James Henson <jfhenson1 at gmail.com> wrote: > Dear R Community, > > Below is a problem with a simple ggplot2 graph. The code

Hi all, I analysed my data with lme and after that I spent a lot of time for mean separation of treatments (post hoc). But still I couldn’t make through it. This is my data set and R scripts I tried. replication fertilizer variety plot height 1 level1 var1 1504 52 1 level1 var3 1506 59 1 level1 var4 1509 54 1 level1 var2 1510 48 2 level1 var1 2604 47 2 level1 var4 2606 51 2 level1 var3

Dear R folk, First off I want to thank those of you who responded with comments for my R quick and dirty stats tutorial. They've been quite helpful, and I'm in the process of revising them. When it comes to repeated measures MANOVA, I'm in a bit of a bind, however. I'm beginning to see that all of the documentation is written for psychologists, who have a slightly

r-help at stat.math.ethz.ch on Wednesday, October 26, 2005 at 6:00 AM -0500 wrote: Ronaldo, Try Harold's suggestion. The df still won't agree, because lmer (at least in its current version) just puts an upper bound on the df. But that should be OK, because all those t tests are approximations anyways, and you can get better confidence intervals (credible intervals, whatever) by using the

Hi all Consider the classic data below from Darwin on the heights of 15 pairs of zea mays (corn) plants either cross-fertilized or self-fertilized, where the goal is to see if it makes a difference. > head(ZeaMays) pair pot cross self diff 1 1 1 23.500 17.375 6.125 2 2 1 12.000 20.375 -8.375 3 3 1 21.000 20.000 1.000 4 4 2 22.000 20.000 2.000 5 5 2 19.125

...ble to optimize" can only come from no convergent "best fit" being found in the `factanal.fit.mle` procedure. Some detective work shows that the failure is in the call to `optim`. Specifically, when the call __passes__, it returns: > nfit Call: NULL Uniquenesses: Fertility Agriculture Examination Education 0.420 0.492 0.270 0.005 Catholic Infant.Mortality 0.061 0.960 Loadings: Factor1 Factor2 Fertility -0.674 0.356 Agriculture -0.648 0.297 Examination...

Hi everyone! I tried to look up in the previous topics whether there was something similar to my question but I think there's nothing corresponding... Anyway! Here is my problem: I have a plot (qplot()) in which I want to insert axis labels with the following text: kg NH4+ N-equiv. * ha-1 yr-1 (well... 4 smaller and down and + as a power (the same for the -1) but I am sure you understood

Hi Sean, Thank you for reminding me. It looks like it get lost among tons of emails and other tasks. I’ll check if the code size issues still exist. Thanks, Evgeny Astigeevich From: Sean Fertile <sd.fertile at gmail.com> Date: Monday, 29 January 2018 at 19:52 To: Florian Hahn <Florian.Hahn at arm.com> Cc: Evgeny Astigeevich <Evgeny.Astigeevich at arm.com>, Graham Yiu <gyiu

I am using the gls function of the nlme package to analyze data sets of soil respiration which have the following design: 3 complete blocks x 5 sampling dates (time from fertilization) x 3 fertilization levels. The fertilization dates are equal for all subjects (blocks) but not periodical (-46, 10, 24, 53, 123 days from the event). The code that I've been using is: fit.csnC<- gls(dno.C

Hello everyone I am currently trying to conduct analysis of my graduate thesis data using a mixed effects model and I have reached an impass. When I try to conduct a multiple comparison, I get an error (See below): > fm3<- lme(abovegroundbiomass.m.2~medium*amelioration*fertilizer*treatment, random=~1|block/medium/amelioration/fertilizer) > tukeytest<-glht(fm3,

Hello All, This conversations seems to have fizzled out and I would like to try to revive it. My intention is to pick up where Graham left off with enabling partial-inlining by default. On Sat, Dec 9, 2017 at 7:47 AM, Florian Hahn via llvm-dev < llvm-dev at lists.llvm.org> wrote: > Hi, > > On 13/11/2017 14:47, Evgeny Astigeevich via llvm-dev wrote: > >> Hi Graham,

Greetings, I have a question that I'd like to get input on. I have a classic toxicology study where I artificially fertilized and exposed embryos to a chemical and counted defects. In addition, I kept track of male-female pairs that I used to artificially fertilize and generate embryos with. I need to use logistic regression to model the response, but also check that the genetics of the

Hi there, I have a experimental design related question. I have done a experiment with 3 factors. The design matrix is similar to: > data.frame(Factor.1 = rep(rep(0:2, each = 3),3), Factor.2 = rep(c("U","S","N"), 9), Factor.3 = rep(0:2, each = 9)) Factor.1 Factor.2 Factor.3 1 0 U 0 2 0 S 0 3 0 N