All Questions
Tagged with lme4-nlme interpretation
80 questions
0
votes
1
answer
233
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Multilevel analysis - interpretation not significant at level 1
I'm doing a multilevel analysis for the first time for my master thesis.
The goal of my study was to create behaviour change through an intervention. Participants are measured for behaviour at 3 ...
0
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0
answers
18
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Doubts in interpreting 2 way interaction lme [duplicate]
I have some doubts in interpreting my data. So, if I have this model ...
1
vote
2
answers
2k
views
Interpreting output from lmer
This probably has been asked many a times, but I cannot find the answer. I'm trying to interpret the output that I get from lmer.
My code is as follows:
...
2
votes
1
answer
99
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Why is it recommended to keep use.u=T (in bootMer) when doing parametric bootstrap for lmer models?
I am performing a parametric bootstrap with the intention of using the simulated values to create confidence intervals for my coefficients in a mixed model. I saw that it was generally recommended to ...
2
votes
0
answers
110
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confusion about random effects summaries from lme and tab_model SjPlot
I am running into two issues.
As such, I am not confident in my interpretation of summary estimates from the Random Effects part of lme function.
I used the ...
2
votes
1
answer
2k
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How to interpret random intercept "BLUP" from the sjPlot package?
I am using the sjPlot package to estimate my multilevel model and I am loving it. However, I am a bit confused by the output of the random intercept.
Background:
My dependent variable is on a scale ...
0
votes
1
answer
1k
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How do I interpret these linear mixed model coefficients from r?
I've fitted a mixed model with participants and vowels as random factors and language (Tamil and French) as the fixed factor. The dependent variable is durations of prolongations (of a phoneme). The ...
0
votes
0
answers
47
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How do I interpret output of lmer summary and anova
I have created a linear mixed effects model testing for shannon diversity index, with flower_quantity, temp, precip, wind and cloud cover as continuous variables, and season as a categorical variable. ...
1
vote
0
answers
94
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LME4 : How to interpret a lmer model interaction that includes a numerical variable (linear factor)
I have a model that looks into a 3-way interaction between 2 categorical variables (Group: Gr. A, Gr. B, Gr. C; Area: A1, A2, A3) and a numerical linear interaction (Distance from center - ECC: 1, 2, ...
1
vote
3
answers
518
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Appropriateness of including control variables in lmer as random effects [closed]
I am trying to find out the effects of the condition (3 levels) on a dependent variable (intention to use a certain mode of transportation; assumed to be continuous, 1-7 scale), whilst controlling for ...
0
votes
1
answer
52
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lmer: 3-way interaction to explore if categorical variable moderates treatment effect
I evaluated the effectiveness of an intervention by using lme4 package:
lmer(Depression ~ time * group + (1|id))
resulting in a significant interaction (time * ...
1
vote
0
answers
146
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Interpreting contrasts in lmer
I would like to make sure whether I’m interpreting the results of the lmer model I generated in the right way. The model is:
...
0
votes
0
answers
208
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Glmer result interpretation of mixed effects and intercept
I am having trouble interpreting my mixed-model results. I am a biologist and not really good at statistics yet. I have done a mixed-model using binomial family, as the dataset I am working on is ...
0
votes
1
answer
109
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Compute slopes for both levels of a factor
Here is the linear mixed model that I am working with:
p3 <- lmer(respTime ~ proc*farFC+(1 | Subject), dtINT)
Proc refers to a factor with 2 levels (adjacent ...
3
votes
1
answer
949
views
Interpretation glmer output and CI with interaction for non-reference level
I could use some help interpreting a glmer output? I am unsure how to get the odds of a non-reference level since there is an interaction. I have observations of ...
1
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0
answers
169
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How to interpret linear mixed model with/without random intercept fitted in nlme
I fitted two models using the Oats data from nlme:
...
1
vote
0
answers
20
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How to interpret LME Estimates for an interaction effect that contains two continuous variables when one variable can be positive or negative [duplicate]
I am somewhat confused about how best to interpret the results of my logistic mixed effects model.
I have two variables, confidence (continuous, 0-100) and meta-d', which can range from -0.5-2. From ...
0
votes
1
answer
185
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LMM Results interpretation: Change in results when adding interaction
This question is a follow up question from this one: Controlling for an effect by adding it as covariate in R
Now that I know my model is coherent, I have some issues interpreting my results.
The ...
3
votes
1
answer
119
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Mixed model fixed effect interpretation doubt
I'll try to summarize my problem as clearly as possible (and yes, I read a million other threads with similar problems, googled it, and I'm still here begging for help).
I am trying to generate a ...
2
votes
0
answers
659
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lme4: glmer() warning messages with count data mixed-effects model and how to proceed with model fit
I have fitted a GLMM with the function glmer of lme4 package.
My data consists of a repeated measures count variable, which I am trying to explain with a continuous variable (week) and some ...
3
votes
1
answer
656
views
Interpretation of intercept in random-effects only LMM
I am using LME4 to fit models for a repeated measures study in psychology. Before jumping in to my fixed effects, I decided to start by comparing different random effects structures. I fit a number of ...
2
votes
1
answer
685
views
lmer fixed effects t-statistic interpretation
I'm struggling to explain some output from a linear mixed effects model. I've done a lot of reading and searching of previous questions but haven't been able to find what I'm looking for.
I have 3 ...
1
vote
0
answers
284
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emmeans in R - generating and interpreting contrasts [closed]
I hope somebody is available to help a desperate rookie..
I fitted a glmer with a Poisson distribution and log link, including main effects and several interactions, an offset variable and a random ...
2
votes
1
answer
1k
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interpret interaction effect in linear mixed model with dummy-coded categorical predictors with lmer
I've looked through quite a few websites and threads here, but I find the interpretation of interaction effects in linear mixed models with categorical factors quite tricky and would be glad if ...
2
votes
1
answer
3k
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Interpretation of DHARMa residuals for Gamma GLMM
I am fitting a Gamma GLMM (lme4::glmer) with log link and doing model diagnostics with DHARMa. I am getting significant results indicating my residuals are not ...
6
votes
1
answer
2k
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Interpretation of binomial GLM (glmer) with interaction and results description
I would like to confirm if I am analysing the results of my model correctly and get some advise if I am missing something!
I conducted the following model to analyse factors that describe the feeding ...
2
votes
0
answers
639
views
Significant interaction but no significant simple effects in lmer
In my liner mixed effect model, there are two independent variables location (2 factors: E, word) and cond_aud (3 factors:CA,EA,...
3
votes
1
answer
105
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Specifying (and interpreting) LMMs using factorial designs with nlme/lme4 - should variables be coded as factors?
I’m trying to specify (and interpret) a LMM using data with the following factorial design:
• Condition (Active/Sham: between-subjects)
• Session (1/2/3: within-subjects)
• nbacklevel (1/2: within-...
3
votes
1
answer
635
views
How do I obtain the estimate for each level of an interaction term containing a categorical variable in LMER R?
I fit a linear mixed effect model to my data with random slopes.
...
1
vote
0
answers
962
views
Interpretation of GLMM summary in R [closed]
I have serious difficulty understanding the default R-summary of a GLMM model from the lme4 package.
First of all, I would like to know how to interpret the ...
2
votes
0
answers
24
views
How to construct GLMM with differing random effect variance structure by group?
I have a longitudinal dataset with a normally distributed outcome variable, a normally distributed predictor variable, and a binary grouping variable. I am trying to construct a GLMM with differing ...
5
votes
0
answers
2k
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Interpreting the variance of random effects in Mixed Linear Models?
When fitting the following simple model, using the 'lme4' R package and including a fixed and random slope term, I get:
...
3
votes
1
answer
3k
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emmeans output interpretation of a glmer fit with nesting
I have read that the interpretation of generalized linear mixed models (GLMM) at the response level is more complex because the back transformation is nonlinear and the random terms do not play a ...
5
votes
1
answer
751
views
Should I remove random intercepts from my model?
I have collected some data on response times (Y) under two varying conditions (X1 and X2). The conditions are continuous variables, although I set them to fixed values of 1,2,3,4 and 5.
I have 10 ...
0
votes
1
answer
158
views
interaction effect in linear mixed models - interpretation
I ran the following model:
...
0
votes
0
answers
261
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Interpreting orthogonal polynomial interaction terms with continuous predictors?
I'm struggling with the interpretation of orthogonal polynomial interactions when both predictors are continuous and would like to make sure my interpretation is correct. Thank you in advance for your ...
3
votes
0
answers
113
views
Can I validate a residual plot although it has residual patterns if I am not interested in model's coefficients using `lme4::glmer()`?
I am studying how well I can predict the height above ground (km) of an animal (=bird) using a technique (method B) which samples data every certain time-intervals. ...
0
votes
0
answers
53
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Need help interprete lmm result - One fixed effect one random effect
I am investigating the difference in size between pike fry during their emigration period out from their nursery area. My hypothesis is that bigger fry tend to force smaller sized fry to migrate due ...
3
votes
1
answer
420
views
Relevance of Mixed Model Estimates vs. Observed Means [duplicate]
This question is a follow-up to a previous question I asked regarding mixed model effects construction, linked here. It provides some background, although this is a broader question with little to do ...
1
vote
0
answers
502
views
report output GLMER and do contrasts
I'm running a glmer and have a few questions regarding how to interpret the output and how to report it:
it's not clear to me what the main effects are given that they are all in reference to a base ...
11
votes
1
answer
23k
views
How to interpret 2-way and 3-way interaction in lmer?
I have a problem with interpreting 2-way and 3-way interactions in lmer. My DV is height which is a continuous variable. All IVs are categorical variables. The first factor is animal, either rat or ...
1
vote
1
answer
1k
views
lmer: comparing model fit and null hypothesis significance testing
We recently used lmer to analyze some reaction time data. There were three fixed effects variables, and the model included their interactions and a fully specified random effects structure. Something ...
3
votes
1
answer
1k
views
Filling missing data points with lmer prediction model
I'm trying to interpolate the missing data point using lmer model prediction.
Subsetting to a table without any na to the missing column of interest:
...
0
votes
1
answer
559
views
Interpretation of binomial GLMM with interaction fitted with glmer
I have a glmer model from the R package lme4 with a binomial distribution and I was wondering whether I am interpreting the ...
2
votes
0
answers
55
views
Difference in joined or splitted random slopes in mixed model (lme4 notation)
I would like to understand better the consequences of formula syntax choices in lme4 package.
Imagine I want to model outcome Y as a function of X1 and X2 = f(X1), with and without interaction, with ...
0
votes
0
answers
44
views
Correct interpretation of coefficient estimates from GLM on binary outcome data [duplicate]
I'm currently analysing an experiment where animals were presented with a stimulus under two different treatments (Po & Br) ...
1
vote
0
answers
85
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Orthogonal polynomials lme4: Interpretation of significant quadratic predictor when linear predictor is not significant [duplicate]
Summary of Study
Participants worked in pairs to complete three tasks. Periodically throughout the interaction, they evaluated one another across a variety of categories. The primary category of ...
1
vote
0
answers
389
views
Model ANOVA or marginal ANOVA for detecting significance
I have recently faced a weird way of finding a significant variable.
Let the model be
$Cholesterol=Sex+FamilyHistory + Sex*FamilyHistory$
where the * denotes the interaction, sex and FamilyHistory ...
0
votes
1
answer
349
views
How to interpret a GLMM
I am new to stats and have run a GLMM in R using the lme4 package. The model includes marine litter collected in KG, with fixed variables of population (all), wind direction, wave strength. Random ...
0
votes
1
answer
627
views
How to interpret quadratic effects?
I have built a LMM (using LME4) for understanding how investment fund's structural characteristics (things like how much debt they have, their size etc) impacts upon performance.
In the analysis, I ...