similar to: Multiple comparisons when interacction]

In the model: lm.1 <- lm(variable ~ BLOC + TIL * YEAR , data=selvanera) I found TIL*YEAR interaction significant. Then I am trying to compare means of the different levels of TIL inside every YEAR using: mc.2 <- glht(lm.1, linfct = mcp(TIL*YEAR="Tukey")) summary(mc.2, test = univariate()) but it does not work. There is any way of doing this, like the SLICE option in

I am returning this to the R-help list. Please keep followups on the list. Yes, it can be done. It is not currently easy because multcomp doesn't have the syntax yet. Making this easy is on Torsten's to-do list for the multcomp package. See the MMC.WoodEnergy example in the HH package. The current version on CRAN is HH_1.17. Please see the discussion of this example in R-help:

Hello, With this program I try to repeat analysis for different years. The results of the analysis are not printed when in the loop, except for the year sequence. What is wrong? Thanks a lot. for (i in 92:99){ cat("\n", "=============================================================\n", "YEAR =",i,"\n",

I have several devices, mostly amd64 and armhf architectures, all of which updated samba to 4.17.6 without any problems. But one which is armel architecture failed to update; instead I get the following when I try to update: root at goflex:~# samba -V Version 4.17.5-Debian root at goflex:~# apt update Hit:1 http://ftp.uk.debian.org/debian bullseye InRelease Get:2 http://ftp.uk.debian.org/debian

Hi- I'm wondering if anyone can help me with my code. I'm coming up dry when I try to get a p-value from the following code. If I make a histogram of my resampled distribution, I find the difference between by groups to be significant. I've ranked the data since I have outliers in one of my groups. mange= c(35, 60, 81, 158, 89, 130, 90, 38, 119, 137, 52, 30, 27,

Thanks it worked for me. I wanted to plot days since planting on x-axis 1 and years on x-axis 3. LAI_simulation$Date <- as.Date( LAI_simulation$Date, '%Y/%m/%d') LAI_simulation$Date <- as.integer(LAI_simulation$Date - as.Date("2009-10-07")) plot(LAI~Date,data=LAI_simulation,xlab="Days since Oct, 7,

Hi, I'm analyzing a longitudinal data set with 387 cows were observed in 63 days divided into 6 groups, and every 30 days was found to produce milk. Does not aim to model the time using regression. Only compare the groups differ in terms of milk production. There are many missing observations. Because the data are correlated I used the SAS program: proc mixed data=univar

The model should be class aov or lm and my model class is aovlist. tried tidy from broom library but did not work. To make it class aov, I had to remove the error term; model <- aov(Rotationdata_R$`GY(Mg/ha)`~Rep+code*as.factor(Nitrogen),data=Rotationdata_R) Ahmed Attia, Ph.D. Agronomist & Soil Scientist On Mon, Dec 25, 2017 at 7:38 PM, David Winsemius <dwinsemius at

Hola a todos: Necesito saber si alguien tiene alguna idea de un paquete con múltiples funciones (cálculos) para determinar el tamaño de la muestra (particularmente de estudios de psicología y ciencias sociales). De antemano agradezco la atención. Saludo desde Brasil *Guilherme Amorim Homem de Abreu Loureiro* Agronomist Engineer *CREA-BA: 051511013-2* Master of Science in Crop Production, Soil

Hi Ahmed, Your problem appears trivial as you have already specified the form of the calculation. Learn how to "extract" specified elements from a data structure: # first value sum(dataset1$NPP[dataset1$date >= date1 & dataset1$date <= date2]) # second value dataset2$biomass[dataset2$date == date2] - dataset2$biomass[dataset2$date == date1] # third value

Sorry for the confusion, here is the edited question. The data= Stand_Height (attached) is recorded from 12/1/2009 to 12/31/2015 (25 observations) and the other dataset (leafbiom) is recorded from 10/7/2009 to 12/29/2016 (daily observations). I want to use the 25 observations of stand height to predict the daily stand height from 10/7/2009 to 12/29/2016. The daily stand height will be multiplied

Hi R users, I need your help to write a code in r that does the following calculation from three different datasets; ac = 1/sum (NPP from date 1 to date 2, dataset=1) * (biomass at date 2 -biomass at date 1, dataset = 2) + (littfall at date 2, dataset=3). all the dates are in yr-month-day format. Which library or function Should I use to tell R do these calculations of these variables at

Hi folks, I have 25 stand height observations over 7 years period and daily leafbiomass data during this period. I want to use the 25 plant height observations as inputs and predict the daily stand height during the 7 years. SH=matrix(data=NA , nrow = 2641, ncol = 1) for (i in 1:2641) { SH<- predict(lm(height~Date, data=Stand_Height)); dl=leafbiom$Date[i-1]; de=leafbiom$Date[i];

LSD-test produces error for this code; code <- as.factor(Rotationdata_R$`Rot/code`) #factor in the main Nitrogen <- as.factor(Rotationdata_R$Nitrogen) #factor in the sub Rep <- as.factor(Rotationdata_R$REP) #blocks Year <- as.factor(Rotationdata_R$YEAR) #years model <- aov(Rotationdata_R$`GY(Mg/ha)`~Rep+code*as.factor(Nitrogen)+Error(Rep/Year/code),data=Rotationdata_R)

> On Dec 25, 2017, at 2:09 PM, Ahmed Attia <ahmedatia80 at gmail.com> wrote: > > The model should be class aov or lm and my model class is aovlist. > tried tidy from broom library but did not work. To make it class aov, > I had to remove the error term; > > model <- aov(Rotationdata_R$`GY(Mg/ha)`~Rep+code*as.factor(Nitrogen),data=Rotationdata_R) You seemed to have

How can I convert date to continuous variable staring from 1. I tried as.numeric but R starts counting from default January 1, 1970 while my data start Oct 7, 2009. I need to do this conversion to plot the date on two x-axes (1 and 3). Ex; Date LAI 10/7/2009 0 10/8/2009 0.004173 10/9/2009 0.009997 10/10/2009 0.009998 10/11/2009 0.009999 10/12/2009 0.009999 10/13/2009 0.009999 10/14/2009 0.009999

Hello R users, The code below is for loop in R that I want to do to following calculation at each time i and i-1 in 2:75 dataset (Litterfall_Ahmed97). ac = ((LeafBiog at date i -LeafBiog at date i-1, dataset = leafbiom97) + (littperiod at date i, dataset= Litterfall_Ahmed97))/(sum (GPP from date i-1 to date i, dataset=GPP_Ahmed13)/2) . #code for loop GPP_Ahmed13$Date <-

There are a bunch of things wrong here, although without a reproducible example I can't really fix most of them. - You're overwriting SH within the loop. - You're running the regression 2641 times, even though the result never changes. - You're never predicting from your linear model using the other data not in the regression. - Leaf biomass data is never used for anything. I

I suggest perceptual diff. You could write a wrapper around it. http://pdiff.sourceforge.net On Mon, 7 May 2018 16:49 Ramiro Barrantes, <ramiro at precisionbioassay.com> wrote: > Hello, > > I am working on tests to compare figures. I have been using ImageMagick, > which creates a figure signature, and I can compare a "test" figure > signature against a saved

I have numerous replicated goodness-of-fit experiments (observed compared to expected counts in categories) and these replicates are nested within a factor. The expected counts in each cell are external (from a scientific model being tested). The calculations I need within each level of the nesting factor are a heterogeneity G test, with the total G and the pooled G across replicates. Then I