[R-sig-ME] How to pairwise comparisons with lsmeansLT

[Lenth, Russell V]

The interface style you mention is for the 'lsmeans' function in the *lsmeans* package. The developers of the *lmerTest* package renamed their 'lsmeans' function 'lsmeansLT' to help avoid confusion.

Russ

Russell V. Lenth  -  Professor Emeritus
Department of Statistics and Actuarial Science   
The University of Iowa  -  Iowa City, IA 52242  USA   
Voice (319)335-0712 (Dept. office)  -  FAX (319)335-3017



Message: 1
Date: Thu, 09 Feb 2017 13:46:31 +0100
From: Jo?o C P Santiago <joao.santiago at uni-tuebingen.de>
To: r-sig-mixed-models at r-project.org
Subject: [R-sig-ME] How to pairwise comparisons with lsmeansLT
Message-ID:
	<20170209134631.Horde.DnanEC4xDkyQa7A8g5pMG6F at webmail.uni-tuebingen.de>
	
Content-Type: text/plain; charset=utf-8; format=flowed; DelSp=Yes

Hello everyone,

Last I used lsmeans from the lmerTest package one could simply

lsmeans(mod, pairwise ~ a | b)

and get a nice output with pairwise comparisons and adjusted p-values.

now it seems lsmeans is deprecated, replaced by lsmeansLT.

lsmeansLT(mod, test.effs = "a:b")

does not have the same output. Here my own output

> lsmeansLT(fit_linN, test.effs = "stageGroup:treatment")
Least Squares Means table:
                                         stageGroup treatment Estimate  
Standard Error   DF t-value Lower CI Upper CI p-value
stageGroup:treatment  Awake Control            1.0       1.0    44.75   
         10.00 27.7    4.48     24.3     65.2   1e-04 ***
stageGroup:treatment  REM Control              2.0       1.0    90.92   
          6.25 72.1   14.56     78.5    103.4  <2e-16 ***
stageGroup:treatment  S1/S2 Control            3.0       1.0   272.32   
          8.79 31.5   30.97    254.4    290.2  <2e-16 ***
stageGroup:treatment  SWS Control              4.0       1.0    86.62   
          8.44 33.2   10.27     69.5    103.8  <2e-16 ***
stageGroup:treatment  Awake Stimulation        1.0       2.0    52.15   
         10.00 27.7    5.22     31.7     72.6  <2e-16 ***
stageGroup:treatment  REM Stimulation          2.0       2.0    89.85   
          6.25 72.1   14.39     77.4    102.3  <2e-16 ***
stageGroup:treatment  S1/S2 Stimulation        3.0       2.0   265.82   
          8.79 31.5   30.24    247.9    283.7  <2e-16 ***
stageGroup:treatment  SWS Stimulation          4.0       2.0    86.40   
          8.44 33.2   10.24     69.2    103.6  <2e-16 ***
---
Signif. codes:  0 ?***? 0.001 ?**? 0.01 ?*? 0.05 ?.? 0.1 ? ? 1

the interaction stageGroup:treatment is NOT significant, the plots show no signs of interaction. I think what is being tested here is wrong anyway. what I want is to test the differences in means between treatments in each stageGroup.
the former version of lsmeans would do this. for example lsmeans(mod,
"treatment") would only tests the difference between treatments after adjusting for the other covariates.

Am I doing something wrong here?

Additionally: if this is not the way to go to obtain p-values from multiple comparisons (my peers want those values), is it "allowed" to perform multiple t-tests on the normal means? It's not the same though, no adjusment for the other covariates.

Best,
Santiago

-- 
Jo?o C. P. Santiago
Institute for Medical Psychology & Behavioral Neurobiology
Center of Integrative Neuroscience
University of Tuebingen
Otfried-Mueller-Str. 25
72076 Tuebingen, Germany

Phone: +49 7071 29 88981
Fax: +49 7071 29 25016