Refers to a class of models developed to account for correlation that may occur within nested data.

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17 views

how to code a random intercept and slope in a mixed linear model and apply LAM in SAS

I m a PhD student in New Zealand. I need to determine the impact of lameness in milk yield of cows. I measured milk yield daily as well as I recorded the cows that were observed lame in any one day . ...
0
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0answers
17 views

Cummulative Mixed Model in R variable names

I'm trying to fit a cumulative link mixed model clmm() in Rstudio. I'm currently having issues with the diagnosing what is wrong with my model from the output I am getting. The output I got from my ...
2
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1answer
23 views

Missing observations in a linear mixed model

Suppose you are measuring temperature $T_{ij}$ for $i =1, \dots ,4$ subjects and $j= 1, \dots ,4$ time points. For subject 1, suppose $T_{12}$ and $T_{14}$ were missing. Would you omit the entire ...
1
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0answers
20 views

Repeated measures with single measurements

I have the following situation: General practitionar (gp), patient (pat) and consultation (cons). Each gp has several patient and each patient can have 1 and more consultations with a specific ...
2
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0answers
40 views

Reporting results of linear mixed-effects model

Linear mixed-effects models aren't commonly used in my corner of biology, and I need to report the statistical test I used in a paper I'm trying to write. I know that awareness of multilevel modeling ...
0
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0answers
26 views

Cannot do Tukey test in multcomp

After performing series of linear mixed models in lme4 to justify which model with which level of interaction to be used, now I would like to do the Tukey's test for multiple comparison. So first, I ...
0
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0answers
15 views

post-hoc test on mixed-effects model

I have an experiment with bacteria for which I measured growth curves of several bacterial clones in two different types of media (treat). I then extracted several growth parameters from the curves ...
1
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0answers
15 views

Partitioning variance from logistic regression

Short version How can I partition the variance from the different levels in a nested mixed-effects logistic regression? Preferably using R, but even general principles would be helpful as a start. ...
1
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0answers
15 views

Non-independence of data in regression model

I have a problem concerning non-independence of data in an experimental economic game. Participants are in groups of three and interact with each of the other two. Each interaction between persons A ...
0
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0answers
34 views

Fitting non-normal data in lme4 with a family distribution

I'm currently working on fitting a model where we predict the level of some biomarker as a function of time (see image at bottom). I have two difficulties: Each person contributes 2-3 datapoints ...
3
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1answer
75 views

Using glmer to estimate treatment interactions

In my data, I have two treatment conditions with repeated measures for each subject. I would like to run a mixed logistic regression separately for each of my two conditions where my binary outcome DV ...
1
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0answers
12 views

Moderation using ANCOVA

I am performing a repeated measures ANCOVA with Mood Scores as the dependent variable, Image Condition as the independent ...
1
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1answer
25 views

How to expand sample subset with similar data

I would like to categorize a large sample and make some estimates for each category aka subset. The problem is that some subsets contain very few data points. How do I deal with that? For example: ...
1
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1answer
69 views

How do I “nest” data in a mixed-effects model? and MANY related questions about mixed effects models!

I treated 80 people with drug X and 80 with drug Y. I presented the drugs to them in groups of 10 (meow groups). The drug was consumed for 15 weeks. They reported the severity of their headaches (from ...
1
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0answers
10 views

Random effects assumption and testing level 2 predictor variables

I was wondering if someone has any advice about the analysis I’m carrying out, or just give a recommended reference? I’m using a random effects modelling approach to account for clustering of patients ...
0
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1answer
33 views

Is it worth reporting small fixed-effect $R^2$ (marginal $R^2$), large model $R^2$ (conditional $R^2$)?

In a mixed model analysis (lme4 + lmerTest for R), I want to analyse the effect of 3 predictors, say A, B and ...
1
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1answer
24 views

Is it better to use data imputation for missing data or an analysis that is not affected by missing data (e.g., HLM/mixed effects modelling)?

I have treated two groups of 100 people with different treatments. I have pre-treatment and post-treatment data for most participants (as well as 1-month follow-up. I also have weekly data for some ...
0
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0answers
71 views

Difficult interpreting linear mixed model result - R lme function

I'm fitting an harmonic regression model on data from different plants separately as follows: ...
1
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0answers
16 views

Linear Mixed Models with variable time points in SPSS

I am analyzing a clinical study measuring patients' symptoms and brain structure sizes over three time points. The "visits" should be at baseline, 3 months and 12 months but they vary considerably and ...
1
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1answer
61 views

Statistically prove the effectiveness of a treatment using GLM repeated measurements

I have two lots of samples: one is the control lot and the other undergoes some treatment. I did three measurements for the samples: one at the initial time (T1) ...
1
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0answers
7 views

Specifying variance structure in mixed effects Cox model in R [migrated]

I am fitting a mixed effects Cox model in R using the function coxme() in the coxme package. In my model I have a censored survival time $X$, a single covariate ...
1
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0answers
29 views

How to incorporate time varying group covariates in linear mixed effects model

I have a continuous response $Y_{ij}$ after taking repeated measures in an individual $i$. Altogether I measure $Y_{ij}$ 5 times (j=1..5) under different types of subject motion: still1, still2, nod, ...
0
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1answer
51 views

How to predict binary outcome from a glmm model

Suppose I fit a generalized mixed logistic model such like that: ...
3
votes
0answers
39 views

A lot of iterations before converging - GLMM vs GEE question

I'm wondering if there is any implication if a model takes 100+ iterations to converge. Can I still trust the results? I'm running cumulative logit with random intercept in proc glimmix in SAS. ...
1
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1answer
47 views

Binomial GLMM: Model validation & ceiling effect

My data has a binary response acc(correct/incorrect), one continuous predictor score, three categorical predictors (...
1
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1answer
85 views

Binomial GLMM with categorical predictors: p-values?

My data has a binary response (correct/incorrect), one continuous predictor score, three categorical predictors (race, ...
1
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0answers
32 views

Binomial mixed model with categorical predictors: model selection and getting p-values [closed]

My data has a binary response (correct/incorrect), one continuous predictor (with NaNs) and several categorical predictors. I want to add a random intercept for a ...
1
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0answers
31 views

random effect in mixed linear model SPSS

I am using a mixed linear model to analyze the effect of two types of treatment on symptoms. The two treatments were administered in smaller groups (clusters), and delivered by several doctors, so I ...
1
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0answers
25 views

What plots should be used for diagnostics for linear mixed model?

Before fitting a linear mixed model, can any plots be used to show a random intercept/slope is justifiable in the model? I.e. these plots may indicate a different pattern for each individual over ...
0
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0answers
56 views

testing differences between levels of a factor in a linear mixed model

I'm trying to wrap my head around using a linear mixed model and appropriate post-hoc tests to determine if there is a significant difference between various treatments in an experiment I inherited. ...
0
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0answers
57 views

Use predicted values with or without random part to plot Residuals with binnedplot of a logistic regression in glmer (lme4 package) in R?

Which binnedplot of the glmer should I use to check the model? The residuals against the predicted values without random part(REform=NA) or residuals against the predicted values with random ...
1
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0answers
27 views

Exact derivation for finding k-means from Gaussian Mixtures

I am having difficulty in deriving k-means from Mixture of Gaussians. I am following the notation from Bishop (2006), Section 9.3.2: Suppose we have : $$ p(\mathbf{x}| \boldsymbol{\mu}_k, ...
0
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0answers
19 views

How to do cross validation for repeated measurement (proc mixed)

I had run the mixed model for repeated mesurement using SAS proc mixed, I got the model(s) already for my dependent variable. However, proc mixed doesn't provide R^2. Is there any cross validation ...
0
votes
0answers
8 views

Two stage model with a randomly transformed independent variable

Hi all and thank you in advance for helping! I have three variables: $y$ the dependent count variable, $x$ the independent positive continuous variable, $U$ is the observation unit (and I expect a ...
1
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0answers
23 views

Calculating point estimates from model-averaged parameters

I'm using an IT-approach and multi-model inference with some count data. I have used model averaging to obtain parameter estimates from several GLMMs with Poisson-lognormal errors (Poisson family ...
0
votes
0answers
27 views

Repeated measures model

I am trying to analyze some data and wondering if I have the right approach. Each subject viewed seven messages. The outcome variable is acceptance of the message. We want to see if acceptance of ...
1
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0answers
53 views

Fitting multilevel models to complex survey data in R

I'm looking for advice on how to analyze complex survey data with multilevel models in R. I've used the survey package to weight for unequal probabilities of ...
0
votes
0answers
28 views

Growth curve analysis on orthogonal polynomial terms

I am conducting a study which is looking at the effect of 'Condition' (Quiet, Intelligible, Unintelligible) on the pupil(eye) response over time. Upon visual inspection of my data plots, pupil ...
1
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0answers
37 views

Fixed, random effect and nested factor in lme

I have a dataset with the following variables: Treatment : (fixed,3 levels) Location : (fixed, 4 levels) Sample (random, 5 levels): 5 samples are taken in each location (randomly) Subsample ...
3
votes
0answers
35 views

Different estimates of crossed random factor variance using nlme and lme4

I want to fit a model with two crossed random factors that also allow heteroscedasticity. Whereas nlme4 allows non-constant error variance, I was not sure how to ...
1
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0answers
30 views

How to visualize an interaction from a GLMM: use whole model to obtain predicted values or just factors in the interaction?

I need to plot an interaction between two continuous factors for interpretation. I am using the wireframe function in the lattice package and plotting the predicted values from the model with the best ...
4
votes
2answers
94 views

extremely left-skewed response variable - how do I model this dataset?

This is a histogram showing my response variable. The response is # (or proportion? or percent?) of aphids eaten off of cards in fields, to model predation by natural enemies. Predictors: fixed ...
4
votes
1answer
94 views

Variance components estimation in Poisson mixed models

In the mixed Poisson regression model, with vector of random effects $w \sim N(0, \Sigma)$, how are the parameters in $\Sigma$ estimated? Is it the same REML method as in the linear mixed model?
0
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0answers
17 views

Linear Mixed Model Construction Suggestion

I'm currently working on some data that requires me to use linear mixed model. Explanation of Data Experiment of Drugs on Mouse I have 3 drugs and 1 control Unbalanced number of mouse for each ...
1
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0answers
40 views

Machine Learning : Classification algorithm for very high dimensional data which is uniquely definable in a very small sub-space

I am new to machine learning, so forgive me if i am doing something absolutely absurd. I have a classification task (~100 classes) and have about 2 million training data points in a 2000 dimensional ...
0
votes
1answer
47 views

Cross-validation for mixed-effect logistic regression? [duplicate]

I would like to use cross-validation to test how predictive my mixed-effect logistic regression model is (model run with glmer). Is there an easy way to do this using a package in R? I've only seen ...
2
votes
0answers
62 views

Suitable method for modelling (underdispersed?) count data with lots of zeros and long tail

I have a small data set of counts of bees. I tried a simple Poisson model without random effects but it was very overdispersed (3.95). When I fit a GLMM with random effects (using glmer in lme4) it ...
1
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1answer
75 views

Mixed-effect logistic regression in R - questions

I am new to R, and don't see these questions answered anywhere in documentation (though I could be wrong). I am using the following nomenclature to run my mixed-effects logistic regression, based on ...
1
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0answers
93 views

What do the tests of model effects and parameter estimates really tell (when an interaction is defined)?

A couple of times in LMM or GEE (with SPSS, though I doubt that matters – and might occur in other analyses as well, but these are the ones with which I have seen it) I have seen something that seems ...
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0answers
17 views

Need help with proper syntax for SPSS Mixed [closed]

I am having trouble building my model properly, and I was hoping I could get some advice here. I have a 2 (S: P vs. D) x 3 (ET: CA vs. CO vs. AD) between-subjects design. Participants were run in ...