similar to: Fisher's LSD and tukey output thing

Hi, I am trying to reproduce a tukey test in R ========================== x=c(145,40,40,120,180, 140,155,90,160,95, 195,150,205,110,160, 45,40,195,65,145, 195,230,115,235,225, 120,55,50,80,45 ) y2=c( rep(as.character(1),5), rep(as.character(2),5), rep(as.character(3),5), rep(as.character(4),5), rep(as.character(5),5), rep(as.character(6),5) ) crd2=data.frame(x,y2)

http://www.harding.edu/fmccown/R/#autosdatafile http://www.harding.edu/fmccown/R/#autosdatafile I am tring to get a barchat by factors, following the example in that link above. =========================== x=c(145,40,40,120,180, 140,155,90,160,95, 195,150,205,110,160, 45,40,195,65,145, 195,230,115,235,225, 120,55,50,80,45 ) y2=c( rep(as.character(1),5), rep(as.character(2),5),

Hi there, Is there a function that can do a Fisher's LSD multiple comparisons in a two-way ANOVA? I hope to get a result similar with TukeyHSD(). Especially, I hope to know the significance of comparisons between the interactions of two factors. In the following example: x <- c(76, 84, 78, 80, 82, 70, 62, 72, 71, 69, 72, 74, 66, 74, 68, 66, 69, 72, 72, 78, 74, 71, 73, 67, 86, 67, 72,

Hola de nuevo R-Users, me he dejado cosas para aclara. Primero de todo tengo cinco repeticiones y 20 missings, así que mi n es de 5×10×3×5-20= 730 datos en total, todos los grupos tienen al menos 3 representantes. Segundo: Las variables estudiadas son Producción neta, Peso de 100 semillas y Proteína. Tercero: Observo los mismos genotipos (G) en varios años (A) en las misma localidades

Queridos R-users: Tengo una duda que hace mucho tiempo que estoy intentando resolver, os explico a modo de ejemplo: Tengo estos efectos: Año(5 niveles),Localidad (10 niveles) y genotipo (3 niveles), año y localidad son aleatorios y genotipo es fijo (los he escogido yo). Me gustaría hacer obtener una tabla parecida a la Tabla Anova donde aparezca cada factor y sus interacciones y

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 10:21 AM, Ahmed Attia <ahmedatia80 at gmail.com> wrote: > > LSD.test ?LSD.test No documentation for ?LSD.test? in specified packages and libraries: you could try ???LSD.test? -- David Winsemius Alameda, CA, USA 'Any technology distinguishable from magic is insufficiently advanced.' -Gehm's Corollary to Clarke's Third Law

> 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

Please help. I really like R and I have been looking at how to do LSD multiple comparison test with data that has more than one factor. So far, I am unsuccessful. Please help! Me

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:

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

Hi there, I am trying to run LSD.test(model) I used the following commands: attach(model) m1<- glm(ttl.m ~ site+year, family=quasipoisson, data= model) df<-df.residual(m1) MSerror<-deviance(m1)/df The following command did not work: comparison<- LSD.test (ttl.m, site+year, df, MSerror, alpha = 0.05, group=FALSE) I get an error message: Error: could not find function

Hi to all is there a fisher's post hock test or fisher's combination test in R available? Maybe not -- its very easy to do it in excel ... Kind regards Knut

Hi, I'm designing a experiment in order to compare the growing of several clones of a tree specie. It will be a complete randomized block design. How can I decide what model of mean comparision to choose? LSD, HSD,TukeyHSD, Duncan,...? Thanks in advance

Dear all I have an experiment where plots either have or have not regrown (in 40 plots) after receiving 12 different herbicide treatments and a control (no treatment). The data are significant with a Chi2, but to later distinguish if the differences are significant between each of the 12 treatments apart I need to do multiple Chi2 s between each. Is there a way to run those multiple Chi2 or

Hi, I'm using mda library to solve a discriminant analysis. I get results, but the thing is that I want to use Fisher's method to obtain the classification functions and I'm lost in what I should do: libraries to use, ... Can anybody give me a clue?? Thanks. Carlos Niharra L??pez

Hi, I have a table of observed counts for various genetic markers. Instead of doing Fisher's exact test for each marker one at a time and recording the P value manually, is there a script to go through the whole list and generate the P value column automatically? An example of my data: Counts_CHB and Counts_AA are the observed counts for one allele. 2N_CHB and 2N_AA are the total number

Hi I was wondering whether anyone can help me with this problem....it's been driving me nuts, I've been trying to figure it out for months and months without success!! Basically I have a group of participants who attended 2 experimental sessions a few months apart. I took measures of the way they approach two tasks at Time 1 and the same two tasks at Time 2. I have categorical data (a

I have a matrix with 2 columns and I want to do fishers exact test for these with the totals for each row being 100 say. The data has the form: 23 12 32 21 12 2 and these represents the tables: 23 12 77 88 32 21 78 79 12 2 88 98 How do I use apply to speed up aclculation of the fisher.exact test? -- Thanks, Jim. [[alternative HTML version deleted]]

I have a matrix say, 1 4 23 30 and I want to find the previously attainable fisher's exact test p-value. Is there a way to do this in R? -- Thanks, Jim. [[alternative HTML version deleted]]