Questions tagged [mixed-model]
Mixed (aka multilevel or hierarchical) models are linear models that include both fixed effects and random effects. They are used to model longitudinal or nested data.
7,813
questions
1
vote
0
answers
318
views
R Code for ANOVA of data from plot sampling in RCBD
I set up a RCBD experiment in which I evaluated some maize varieties or treatments (V) in replicated blocks(R). I however also sampled (S) 5 plants from each varietal plot. I intend to write a code ...
2
votes
1
answer
469
views
Modeling growth curves with different starting sizes (NLME in R)
I am trying to model fish egg growth over time given a starting egg size in R. I have repeated-measures data from individuals with grouping variable "Zafra.1". I do not know when the eggs started ...
- 21
1
vote
0
answers
82
views
How to calculate a sample size for a longitudinal study with repeated data?
Did you know a program or logiciel that allows to calculate the sample size for a longitudinal study with repeated data ?
And if my subjects are nested in some schools, how I calculate the sample ...
- 41
1
vote
1
answer
55
views
Its my model a Mixed model?
I am running some analysis with mixed model with R. I get differents measures from differents persons (person as random effect), during this analysis and looking plots for each people vs measures I ...
- 39
1
vote
1
answer
446
views
Are covariates in a mixed model estimated between-group, within-group, or somewhere in-between? And why?
Consider a linear (perhaps mixed) model where we have one factor $p$, one covariate $x$, and no interaction. I want to understand how the coefficient estimate $\hat\beta$ of $x$, and its standard ...
- 775
1
vote
1
answer
133
views
How to find the best fixed effect in a mixed model?
I am trying to see the difference between two variables in mixed models.
Background: The models are for an experiment with a randomized complete block design, but there is a bit of missing data. ...
- 111
0
votes
0
answers
222
views
Summary Output for Nested Random Effect in Fixed Effect
I am trying to build a mixed model with random effect nested in fixed effect.
Below is an example dataset.
...
- 101
1
vote
0
answers
66
views
Treating stimuli and participants as crossed or nested random effects in lme4?
I have conducted an experiment where I measured the pupil diameter of 100 participants in response to 9 sounds presented in a random order, all participants heard the same 9 sounds. I would like to ...
- 11
3
votes
1
answer
1k
views
An R package for GLMM estimation with two random effects?
I am looking for an R package to make an estimate on a general linear model with two random effects.
I was used to lme4 (function...
- 583
2
votes
1
answer
62
views
Is the significance of an interaction more important that the fit of a model?
I am new to lme4 and I am not sure if I understand correctly. If I want to know if there is an interaction between A and B, I have to write two models and then compare them with anova and the one with ...
- 87
11
votes
1
answer
713
views
Repeated measures anova: lm vs lmer
I'm trying to reproduce several interaction test between with both lm and lmer on repeated measures (2x2x2). The reason I want ...
- 551
4
votes
0
answers
215
views
Syntax differences between aov and lmer for two-way repeated measures design
I'm working with the following data frame using R. It consists of measurements obtained from 7 subjects with two independent variables (IV1 and ...
- 323
10
votes
1
answer
190
views
Under what conditions does it make sense to fit random intercepts for an interaction, but not the main effects?
I am aware that when specifying the random structure for one factor (B) nested within another factor (A), we can use:
...
- 60.8k
1
vote
0
answers
40
views
Which model is correct?
I have experimental data frame. There are 4 experiments and 4 treatments within each experiment repeated 4 times within each experiment (balanced design). I would like to test the effect of experiment ...
- 121
3
votes
1
answer
240
views
Repeated measures: Use random intercepts model, too many intercepts?
This is a common question, but I couldn't find a question / answer on Cross Validated dealing with the same problem. In short, is 1000 intercepts too many intercepts, that is, can individual be a ...
0
votes
1
answer
420
views
How to check the linearity of continuous variable in linear mixed model
I'm doing a linear mixed model using lme.
In my adjustement factors, I have a continuous varaible (named X1). And I want to check the linearity of this variable using a spline function or a ...
- 41
3
votes
2
answers
424
views
How to combine random effect and nested random effect with lme
I'm doing a mixed linear model. And I have subjects who have been select in 20 schools. So I want to take this to account.
For this, I want to put a random intercept for the "SCHOOL" variable and a ...
- 41
1
vote
0
answers
46
views
Repeated-measures anova and linear mixed effects models with nonrandomized data
I have data from 7 subjects (id) who performed 3 trials of each of 2 different kinds of movement (Factor mov) under 2 different ...
- 323
0
votes
1
answer
186
views
Control variable with different levels in Regression
I have an experiment with two conditions: Control and treatment groups. I am measuring how confident the treatment groups felt while answering the question. It is a three level indicator- not sure, ...
- 71
4
votes
1
answer
1k
views
Random effects in GAM
I'm modelling some biological function, outcome, in patients over 8 hours. Over time, I measure two additional covariates x and ...
- 36.5k
2
votes
1
answer
3k
views
Warning message when using a binomial distribution in glmer() models in R
I asked a similar question in the R forum but realized that isn't the optimal place to post. I'm working with a dataset looking like this:
...
- 177
2
votes
1
answer
47
views
Minimum no. of grouping variables in mixed models
I have data where I collected y and predictors x1, x2, x3...
- 981
1
vote
1
answer
663
views
GEE vs GLMM in large sample size?
I am running two longitudinal models for two different populations I'd like to compare. N1=4,000 individuals (translated into about 20,000 rows; 18 variables) and N2=400,000 individuals (~4 million ...
- 11
3
votes
1
answer
2k
views
Is it okay to fit linear mixed effects model in an unbalanced design as well as few observations (<2) at specific levels?
We are planning to collect behavioural data from ~200 children. We're manipulating 12 stimulus pairs. Based on 3 different models, for each stimulus pair there will be 3 different values to represent ...
- 31
0
votes
1
answer
332
views
Model assumption of linearity
I am trying to interpret the outcome of a test for assumption of linearity. This is the dataframe:
...
- 1
0
votes
0
answers
66
views
forced fixed intercept but lattice plot showed random intercept
I was running a model and something weird pops up.
I ran a multi-level regression using the code below:
...
0
votes
0
answers
1k
views
Calculating R^2 for a linear mixed model in python
I have been looking around online in regards to R^2 calculations in mixed models and a lot of info has come up in R (lme4, MuMIn) where the lme4 package creates the mixed model fit and MuMIn ...
- 1
0
votes
1
answer
53
views
Should I treat these variables as random? (ecology/recruitment question)
I'm working with recruitment data for caribou.
There are 13 different herds, sampled over 20+ years, once per year. Some herds are sampled consistently, some only a few times over 20 years.
I'm ...
- 11
3
votes
0
answers
39
views
Are there extant deep learning analogs to random coefficient (aka mixed) models?
Random coef models, applied to longitudinal data, capture response heterogeneity by cross-sectional unit.
I've got a longitudinal prediction problem, in which I know that some "features" (or ...
- 13.3k
4
votes
1
answer
134
views
Finding GLMMs that fit my count data for multiple datasets
I need some help finding a model that fits my data.
I'm using GLMM's to test the effect of nitrogen level (numerical), species (two-level factor), and the interaction between these two variables, on ...
- 73
3
votes
1
answer
172
views
Out-of-sample predictions for mixed model are the same as naive model (ignoring the random effects)
I have a dataset that consists of subjects coming into the clinic (for treatment of another disease) and they are screened for Tuberclosis (as they are a high risk population). Every time they are ...
2
votes
1
answer
184
views
Construction of linear mixed model (using R)
I would like to use Lineal Mixed model to see if the treatments I applied to some soil changed significantly their CO2 fluxes.
I have 2 temperature (t1, t2) and 3 inundation (w0,w1,w2), resulting in ...
- 25
5
votes
3
answers
1k
views
Mixed models. Random slopes only, mean and group centering?
Are random intercepts a theoretical/practical prerequisite to random slopes? Why?
I have a three level (rep measures) mixed model where I wouldn't expect lvl 3 variation in initial status of outcome ...
- 71
2
votes
1
answer
1k
views
Does nlmer() from lme4 assume normal distribution of residuals and random effects?
I am currently reading this paper
, according to which
Linear mixed-effects (LME)
(Laird & H.Ware, 1982) and nonlinear mixed-effects (NLME) models (Pinheiro & Bates, 2000) are
...
- 23
2
votes
1
answer
49
views
Correlation between random intercept and covariables in generalized mixed models
I'm little bit struggle this 4 past days about a specification of a likelihood in the context of correlation between a random intercept and covariables in generalized mixed models. A known approach is ...
- 635
3
votes
1
answer
2k
views
Understanding nested random effects - why is an interaction between factors involved?
I have read this question and answers:
Crossed vs nested random effects: how do they differ and how are they specified correctly in lme4?
however, I am struggling to understand why, provided that ...
- 60.8k
2
votes
1
answer
504
views
Identical standard error for multiple predictors in mixed effect model
I'm running a 2*2*2*2 mixed effects design in R using the lme4 package, on a number of different sets of similar data--running exactly the same model, just with a ...
- 161
0
votes
1
answer
55
views
Repeated measures regression using GLMM if there are varying numbers of measurements per subject
Aim: To develop a predictive model for an infection, judged condition negative/positive by an assumed gold-standard.
Data: Longitudinal data for a number of subjects, at each time point comprising a ...
- 103
5
votes
1
answer
2k
views
Why do we do crossed vs. nested vs. other random effects?
Let's try a theoretical example. I am trying to predict the math scores of students within schools. I see three ways I can model this with random effects:
(1) I can "nest" the random effects. My ...
- 681
0
votes
0
answers
508
views
Random effects in a linear model using BayesFactor package: why do bayes factors vary?
I'm using the BayesFactor package with the lmBF and generalTestBF functions to compare different linear models that include participant as a random effect. Below is an example of one of these model ...
- 1
1
vote
1
answer
48
views
Model with "Integer Inflated" distribution Y
Forgive the poor statistical lexicon, I am a naturalist.
I am trying to find the best link function to build a model to estimate a response variable (Y) that has what I called an "Integer Inflated" ...
- 266
0
votes
0
answers
588
views
Predicting individual-level outcome with only group-level data
Suppose I have summary data from a number of different classrooms, and I want to model a binary outcome (pass/fail) for individual students. I have no individual-level data. I have some classroom ...
- 101
2
votes
1
answer
5k
views
lme4 lmer() multilevel model: why do I have singular fit and a -1 correlation between random effects slope and intercept?
I'm running a varying intercepts varying slopes multilevel model with the lme4::lmer() function with no group level predictors and only one predictor: FilingFee to predict evictionfilingrate.
I ...
- 23