similar to: Randomized-complete blocks design and R

---------- Forwarded message ---------- From: alis villiyam <aalisiyan at gmail.com> Date: Mon, Jul 27, 2009 at 9:47 AM Subject: randomized block design analysis in R To: bolker at zoology.ufl.edu Dear All user Hello, I'm a student and I have some trouble with the experimental (columns-experiments) design of my project. I use a randomized block design with 4 treatments including a

Hi, I have a matrix of results of multiple 2x2 chi^2 tests, non- significant tests are marked as TRUE. Is there a function for grouping those variables in a similar way LSD.test from agricolae library does? I reviewed LSD.test's source but it's not helpful for me. This is my matrix: [,1] [,2] [,3] [,4] [,5] [,6] [,7] 1 TRUE FALSE TRUE TRUE TRUE FALSE TRUE 2 FALSE TRUE

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

http://bugzilla.mindrot.org/show_bug.cgi?id=71 Summary: configure is looking for zlib but I don't have one and I can't turn zlib off. Product: Portable OpenSSH Version: 3.0.2p1 Platform: Sparc OS/Version: Solaris Status: NEW Severity: critical Priority: P2 Component: Build

The USDA-Agricultural Research Service, Southeast Watershed Research Unit in Tifton, GA, is seeking a postdoctoral research associate for a full-time, 2 year appointment. The research associate will develop, calibrate, and validate a semi-empirical model for estimating cotton biomass from fields within the southeastern United States. Model development will involve the use of optical and radar

> 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

> 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

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

If i insert \u2264 inside the text, like this lsd_label <- "LSD (P \u2264 0.05) = " the result is "LSD (P = 0.05) = " instead "LSD (P ? 0.05) = " how can i solve this problem? Thanks. -- View this message in context: http://r.789695.n4.nabble.com/less-than-or-equal-to-glyph-tp3073557p3073557.html Sent from the R help mailing list archive at Nabble.com.

Dear R Fundation, I am a post-doc researcher at the University of Pisa, Italy. I apologize for my english and I have to tell you in advance that I am a very beginner with R. I used R for fitting dose-response curves (drc package) and for an ordinary ANOVA (one, two or three factors), including the post-hoc mean comparison (I used the LSD test...). Now I have to process some simple data on

I have no problem setting up my mixed model, or performing anova or lsmeans on my model?s outputs. However, performing lsd mean separation is giving me fits. So I do not have a problem when using two-way anova model. When using the code: fit.yield.add <- lm(data = ryzup, Yield ~ Rep + Nitrogen + Treatment) LSD.test(fit.yield.add, trt = "Nitrogen", alpha = 0.1, console = TRUE)

Hi all. I'm working on an assignment for a psychology class and I am not sure how to adjust the y-axis so it displays the range: 0, 5, 10, 15 The code below is almost ideal: lsd = c(3, 5, 13) mar = c(1, 2, 3) g_range <- range(0, lsd, mar) plot(lsd, type="o", col="blue", ylim=g_range, axes=FALSE, ann=FALSE) axis(1, at=1:3,

Perhaps it is just that I don't even know the correct term to search for, but I can find nothing that explains how to wrap around from the end to a start of a row in a matrix. For example, you have a matrix of 2 years of data, where rows are years, and columns are months. month.data = matrix(c(3,4,6,8,12,90,5,14,22, 8), nrow = 2, ncol=5) I would like to take the average of months 5:1 for

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)

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

On 16/07/13 8:10 PM, Erik de Castro Lopo wrote: > Leigh Dyer wrote: > >> Certainly -- I've uploaded the analysis files for both the -6 and -7 >> encodes, in case you wanted to compare: >> >> http://wootangent.net/~lsd/blah/6.ana >> http://wootangent.net/~lsd/blah/7.ana >> >> The encode seems to proceed normally until 59% of the way through the

Hi there, ============================= 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) model1=aov(x~y2,data=crd2) TukeyHSD(model1)

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:

On 16/07/13 6:31 PM, Martijn van Beurden wrote: > On 16-07-13 09:07, Leigh Dyer wrote: >> Hi, >> >> On a particular input file, FLAC (testing with current git) greatly >> inflates its output if I encode at level 7, which enables >> --exhaustive-model-search. The source is a 24-bit WAV file of about >> 60MB; flac -6 encodes this to a 43MB FLAC file, but flac