similar to: 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

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

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 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

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

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

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

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.

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 +

Does anyone have any experience retrieving latitutde and longitude for an address from the Google Maps API? I'd like to have an R script that submits a street address, city, state, and zip code and returns the coordinates. So far, I've been submitting the coordinates from another program, then loading the coordinates in R and merging them back into the data frame I want to use.

Has anyone ever tried putting a circle around a letter or a number in a plot title? For instance, if I have a plot title "Scatterplot for Subject 24", I want to put a circle around 24 to distinguish that plot from the other 30 I've generated. Any tips or ideas beyond plotting a circle in the margin? Benjamin Benjamin Nutter | Biostatistician | Quantitative Health

Dear List, Apologies for this off-topic post but it is R-related in the sense that I am trying to understand what R is telling me with the data to hand. ROC curves have recently been used to determine a dissimilarity threshold for identifying whether two samples are from the same "type" or not. Given the bashing that ROC curves get whenever anyone asks about them on this list (and

*Dear Bert, * Thank you very much for your feedback and the useful link https://rseek.org/ and https://www.r-bloggers.com/calculating-auc-the-area-under-a-roc-curve/. Actually, I want to know different performance between Stata and R, in multilevel logistic regression. For this purposes, I replicate ".do" file use Stata in

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

Hi, Dear all R users: Does someone know whether R can calculate the Receiver Operating Characteristic (ROC) Curves? I didn't find it from the packages. Thanks a lot. --- Xin

Dear User R It's been a pleasure talking with you. I am newcomer use R. Would you please help me how to translate the script below to "R" script? * Area under receiver operating characteristic (AU-ROC) predict r1m1p, p roctab malaria r1m1p, graph summary * Area under receiver operating characteristic (AU-ROC) curve predict r1m2p, mu roctab malaria r1m2p, graph summary

I'm in the middle of my own little intellectual exercise comparing dcast() and reshape() and have successfully stumped myself. I want to melt() a data frame, then dcast() it into a new form. After doing so, I want to duplicate the process using reshape(). So far, I can do the melt and cast require(reshape2) Raw <- data.frame(site = c(1, 1, 1, 1, 2, 2, 2, 2), id =

Hi, can you advise me is there any ROC(Receiver Operating Characteristic)analysis program in R? Thanks, Dechao ===== Dechao Wang Tel: (44) 01223 719718 Mob: (44) 07729 411134 __________________________________________________ Everything you'll ever need on one web page from News and Sport to Email and Music Charts