Questions tagged [lsmeans]
Least-Squares means are predictions from a model over a regular grid, possibly averaged over other dimensions. Also use this tag for the R packages emmeans and lsmeans.
374 questions
6 votes
1 answer
59 views
Different CIs for the same linear mixed model emmeans, ggemmeans, ggpredict
I fitted a linear mixed model in R and tried to compute marginal means using emmeans, ggemmeans (from ggeffects), and ggpredict (also from ggeffects). The predicted means are similar, but the ...
- 61
6 votes
1 answer
85 views
Why are estimated marginal means from a linear mixed / multilevel model and Mixed ANOVA different?
I have trouble understanding the causes of differences in estimated marginal means derived from a multilevel model and from a mixed ANOVA, in particular in a case with only two time points and a ...
- 3,220
0 votes
0 answers
51 views
How to interpret emmip plot for ordinal model
I developed the ordinal model with the interaction of variables A and B. I used emmeans package to obtain pairwise comparisons, I understood how to interpret these. I plotted the emmip plot, and I ...
- 327
0 votes
0 answers
43 views
Parametric bootstrap for multiple comparisons for glmm
When doing post-hoc treatment comparisons with the results from a glmm it is typical in my industry to use PROC GLIMMIX, method=rspl, ddfm = kr, and whatever control method is appropriate (ex. Tukey, ...
- 1
2 votes
1 answer
97 views
Why does cld() in emmeans switch Tukey to Sidak when comparing adjusted means?
I have a model with two predictors, Group (main factor), and Age (covariate). ...
0 votes
1 answer
82 views
Estimate the changepoint where two marginal predictions converge
I have a dataset of participants performing a maximum work task at various loads, under two conditions c("A", "B"). I would like to estimate at what load work becomes the same in ...
- 133
2 votes
0 answers
69 views
Why are the point estimates of estimated marginal means from a Bayesian binomial GLMM so different in the presence of residual covariance?
As the question title says, I am confused why the estimated marginal means (obtained using emmeans()) for a Bayesian binomial generalized linear mixed model are so ...
- 449
5 votes
1 answer
253 views
Why do glmmTMB and emmeans report different p-values?
To illustrate, I have a dataset of eDNA detections of rainbow trout collected using three sampling methods (PES-SP, PES-EtOH, and CN-EtOH). The primary goal of this study is to assess differences ...
- 229
0 votes
0 answers
43 views
emmeans - interaction contrasts to model within-group changes
I was reading several posts regarding emmeans interactions and wanted to make sure I understand the interpertation regarding my model. In my experiment, there are 3 intervention groups and 3 time-...
- 31
3 votes
1 answer
69 views
Do you need to analyse the interaction even when anova shows it's not significant? [closed]
I made a lmer model that, besides other things, includes an interaction between two variables. Anova showed that that interaction is not significant (but both main effects are). The interaction is an ...
- 91
5 votes
1 answer
177 views
AIC prefers full model, interaction not significant — which to use for emmeans
I am using R. I have the following data set: ...
- 155
6 votes
1 answer
186 views
'inf' for degrees of freedom from emmeans based on glmer with binomial distribution
I am getting this 'inf' from degrees of fredom from emmeans when running the following: m1 <- glmer(predation ~ treatment + (1 | individual_code), data = predation_data1, family = binomial) ...
- 61
0 votes
0 answers
41 views
Accounting for influence of a subgroup within a main group and covariates in a linear mixed effect model with emmeans
Sorry if this is a basic question, but I am comparing the traits of two major groups of animals (Group A and Group B). The data I have are collected across thousands of populations of 34 species in ...
3 votes
1 answer
162 views
Pairwise comparisons with emmeans in a linear mixed-effects model
I have a rookie question about pairwise comparisons with emmeans following linear mixed effects modeling. I'm planning an experiment and I'm trying to thing of the correct statistical methods to ...
- 31
6 votes
1 answer
117 views
Inference and multiple comparison tests on GLMM with marginal or conditional interpretations using GLMMadaptive?
As explained in a previous post emmeans output for binomial GLMM : why values are all higher than observations? the marginal (population-averaged) and conditional (subject-specific) interpretations do ...
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