similar to: lsmeans in R

Hi there, I am trying to run simulations using R with linear mixed model (lme). There are two factors in my fixed effect model, educ (treatment and control) and mth (visit 1, 2, and 3). What I want to obtain is the estimated treatment difference (treatment - control) at visit 3, plus the standard error and p-value. This can be easily obtained in SAS using lsmeans or estimate statements, but I

I would like to know how to convert a string with characters to all uppercase or all lowercase? If anyone could let me know if there exists a function in R for the conversion, that will be very helpful. Regards, Suman [[alternative HTML version deleted]]

Hello,   In R, How to read SPSS file and access the data item? Thank you. Regards, Suman Kundu [[alternative HTML version deleted]]

I am using R on unix. While in R how do I execute the unix shell commands? Is there a way to do it? I am executing a function in R and the matrix resulting from the function has to be passed on as an input to unix command. Any directions will be helpful. Thanks, Suman [[alternative HTML version deleted]]

Hi, I wanted to know how to compute the correlation ratio (eta) between two variables using R. Is there any function to compute the correlation ratio. Any help will be very much appreciated. Thanks, Suman [[alternative HTML version deleted]]

Hi folks, I have a dataset that consists of counts over a ~30 year period at multiple (>200) sites. Only one count is conducted at each site in each year; however, not all sites are surveyed in all years. I need to impute the missing values because I need an estimate of the total population size (i.e., sum of counts across all sites) in each year as input to another model. >

It is in the doBy package. Thanks From: Bert Gunter [mailto:bgunter.4567 at gmail.com] Sent: Tuesday, February 13, 2018 4:32 PM To: Pius Mwansa <pmwansa at shaw.ca> Cc: R-help <r-help at r-project.org> Subject: Re: [R] LSmeans and lsmeans Always cc the list unless there is good reason to keep your reply private. There is no LSmeans() function in the lsmeans package.

A cursory reading indicates that they are identical; but others more knowledgeable than I need to confirm or deny this. -- Bert Bert Gunter "The trouble with having an open mind is that people keep coming along and sticking things into it." -- Opus (aka Berkeley Breathed in his "Bloom County" comic strip ) On Tue, Feb 13, 2018 at 3:38 PM, Pius Mwansa <pmwansa at

Always cc the list unless there is good reason to keep your reply private. There is no LSmeans() function in the lsmeans package. Cheers, Bert Bert Gunter "The trouble with having an open mind is that people keep coming along and sticking things into it." -- Opus (aka Berkeley Breathed in his "Bloom County" comic strip ) On Tue, Feb 13, 2018 at 3:20 PM, Pius Mwansa

Hello, I have a big matrix of size (20,5) -bmat . I have to loop though the rows in the matrix and create DIFFERENT matrices each time I go through the loop. counts=c(4,6,10); p=1; for (i in 1:length(counts)) { smat=bmat[p:p+i-1,]; p=p+i; } The problem is smat overwrites itself each time inside the loop. I would like to have smat1, smat2, smat3 instead of a single vector smat.

Hello, This might be a very basic question but I was not sure how to go about it. I just wanted to calcluate the time it takes to run my program. Basically I was to put a timer at the start and the end of the program in order to see how much time it takes to give the output (similar to tic-tac in MATLAB) . Any help will be appreciated. Thanks, Suman [[alternative HTML version deleted]]

Hello, I have a dataset with 20,000 variables.and I would like to compute a pearson correlation matrix which will be 20000*20000. The cor() function doesnt work in this case due to memory problem. If you have any ideas regarding a feasible way to compute correlations on such a huge dataset, please help me out. Please feel free to share your memory handling techniques in R. Thanks, Suman

Dear all, I search the mail list about this topic and learn that no simple way is available to get "lsmeans" in R as in SAS. Dr.John Fox and Dr.Frank E Harrell have given very useful information about "lsmeans" topic. Dr. Frank E Harrell suggests not to think about lsmeans, just to think about what predicted values wanted and to use the predict

Hello All, I wanted to do many plots (in my case, wanted to get 6 histograms) on the same figure. Is there a method in R that analogous to 'subplot' in MATLAB? Any help will be very much appreciated. thanks, Suman [[alternative HTML version deleted]]

Is there a difference between LSmeans and lsmeans functions in R? Thanks, Pius

Hello, I wanted to know how to plot a histogram using a vector of frequencies rather than the data vector as a whole. So I have two vectors: a vector of labels V1= c("A","B","C","D") and vector B which is a vector of frequencies of A, B, C and D respectively V2=c(20,50,60,30). I wanted to plot a histogram of the labels using the frequencies. I could not

I hope you'll forgive me for resurrecting this thread. My question refers to John Fox's comments in the discussion of lsmeans from https://stat.ethz.ch/pipermail/r-help/2008-June/164106.html John you said, "It wouldn't be hard, however, to do the computations yourself, using the coefficient vector for the fixed effects and a suitably constructed model-matrix to compute the

Dear list, Is there a function (or an equivalent way) in R resembling the lsmeans command in SAS? The objective is to get the (adjusted) means for design models. Thanks in advance. Regards, Washington Santos da Silva.

Hello, I have the next function call: lme(fixed=Error ~ Temperature * Tumour ,random = ~1|ID, data=error_DB) which returns an lme object. I am interested on carrying out some kind of lsmeans on the data returned, but I cannot find any function to do this in R. I'have seen the effect() function, but it does not work with lme objects. Any idea? Best, Dani -- Daniel Valverde Saub? Grup

I'm working with a nested model (mixed). I have four factors: Patients, Tissue, sex, and tissue_stage. Totally I have 10 patients, for each patient, there are 2 tissues (Cancer vs. Normal). I think Tissue and sex are fixed. Patient is nested in sex,Tissue is nested in patient, and tissue_stage is nested in Tissue. I tried aov and lme as the following, > aov(gene ~ tissue + gender +