similar to: 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. 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

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

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.

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

Regarding point 3, as a moderator I have been helping Andrew get this post out to the list over the past week. His previous attempts were encoded in some way that the listserv rejected. He sent me the post via his gmail account and viewing the source I saw it had at least both plain test and HTML an I said it was worth a try to post it. Certainly on my mail client his post displays acceptably

I need help with calculating lsmeans (adjusted means) of different terms in a linear model including the main effect and the interaction effect terms. I use lm to run the linear models...I previously noted from literature that that "effects" package can be used to generate lsmeans. But I tried to use it but could not figure out which option to use to get means. If anyone can give an

I will offer an opinion, with which others may fairly take issue. If you are coming from SAS and wish to learn R, you should forget about SAS entirely; it is ancient and convoluted. But more to the point, as others have already suggested, you will only confuse and hamstring yourself trying to convert the programming paradigms of one language into another. Better to consider the **tasks** you wish

Hi, I wonder if anybody could help me in converting this easy SAS program into R. (I'm still trying to do that!) PROC IMPORT OUT= WORK.CHLA_italian DATAFILE= "C:\Documents and Settings\carleal\My Documents\REBECCA\stat\sas\All&nutrients.xls" DBMS=EXCEL2000 REPLACE; GETNAMES=YES; RUN; data chla_italian; set chla_italian;

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. >

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 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 +

Dear all, In connection with a stats course where we want to use R, I am trying to find out if there are analogues to the ESTIMATE and LSMEANS ("population" means) statements in SAS (in proc glm, proc genmod and proc mixed). The students are agronomists, vets and that sort of people, and most of them have some familiarity with SAS. The design package seems to go some of the way, but

-----BEGIN PGP SIGNED MESSAGE----- Hash: SHA1 Hi. I have been using SAS for some time, and now I have discovered R. I am very happy with it, but I have not found out how to perform some of the multiple comparisons I was used to do in SAS. With the SAS/STAT, I generally used the MEANS (for comparison of arithmetic means) and the LSMEANS (for adjusted means) statements of the GLM procedure (I

Hello all, My statistical analysis training up until this point has been entirely done in SAS. The code I frequently used was: *Yield Champagin; data yield; set stress; if field='YV' then delete; if field='HB' then delete; if barcode='16187DD4015' then delete; if barcode='16187DD6002' then delete; if barcode='16187DD2007' then delete; if

You might get better answers if you 1 - break this down into separate issues 2 - tell us what you want to achieve in words rather than SAS, we all read English but few of us speak SAS 3 - post in plain text not HTML as HTML mangles your post On 29/09/2017 13:47, Andrew Harmon wrote: > Hello all, > > My statistical analysis training up until this point has been entirely done > in

--Apple-Mail-27-953181986 Content-Transfer-Encoding: 7bit Content-Type: text/plain; charset=US-ASCII; format=flowed a possible bug with survival analysis - either in R or in SPSS... find more details in bug.doc, and the data in bug.txt best Pius Korner --Apple-Mail-27-953181986 Content-Disposition: attachment Content-Type: multipart/appledouble; boundary=Apple-Mail-28-953181987

Hi I really hope someone can help me. I have just started to work with S-plus, and have not yet understood how it really works. I am now trying to fit a mixed effects model with lme. My goal is to compare four different groups, at several different time points, and I therefore would like to create confidence intervals for linear combinations of my estimated parameters (as I usually do with