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

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5 views

How to turn nlme syntax into manuscript appropriate equation?

I ran an linear mixed-effects analysis in R using the nlme package. I would like to write out the algebraic equation of the model's specifications. Unfortunately, I do not know exactly how to ...
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14 views

How is the confidence interval of variance component calculated?

How is the confidence interval of variance component calculated ? As far I know , confidence interval of variance is calculated as : ...
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22 views

Difference scores in linear mixed models?

I have a question about how to interpret fixed effect interaction coefficients, which appear to be difference scores, in linear mixed models using SPSS. I am looking at the consistency of ...
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1answer
23 views

Why are the Wald standard errors often very poor estimates of the uncertainty of variances?

As from this post as @Ben Bolker pointed out that : .. note that these (as often pointed out by Doug Bates) the Wald standard errors are often very poor estimates of the uncertainty of variances, ...
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1answer
48 views

Difference between two lmer model

Can you please explain where is the difference between the following two models : ...
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7 views
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1answer
20 views

Why CLMM function for ordinal mixed logistic regression changes the means?

I am using CLMM to run the ordinal mixed logistic regression model as the DV is ordinal number from 1 to 9 (rating scale). First I read the file and change the DV into ordinal using these commands: ...
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36 views

Interpretation of various output of “lmer” function in R

library(lme4) fm1 <- lmer(Reaction ~ Days + (Days | Subject), sleepstudy) The notation (Days | Subject) says to allow the ...
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12 views

Correlated errors within group with nonvarying dependent variable

I am trying to run a model in R to show how well one survey (SurveyA) predicts responses to another survey (SurveyB). SurveyA has 20 questions and we get an estimate of the participant's parameter ...
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43 views

3 or, even, 4 parameter distributions [closed]

I have some statistical data for which the pdf has what I think would usually be described as two inflection points. To model this I'm thinking I need something other than the common 2-parameter ...
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14 views

Obtaining significance for mixed GLMMs on count and binary data

I'm new to the software R and am trying to compute statistics on data from experiments on the offspring of lizards from two different thermal treatments - looking specifically at differences in their ...
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1answer
15 views

Interpretation of “Same Slope” in Multilevel Modeling Example

An example of multilevel modeling : Consider an educational study with data from students in many schools,predicting in each school the students’ grades y on a standardized test given their scores on ...
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17 views

linear mixed model with paired and unpaired effects

Here is my problem: 20 subjects performed different movements: arm flexion, abduction and rotations [Ma, Mb, Mc]. In addition each of these movements were performed with or without a load of 3 kg ...
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1answer
81 views

Notation of Variance of Residuals in Multilevel Modeling

I am having some trouble to understand the notation of variance of residuals in multilevel modeling . In this paper "Sufficient Sample Sizes for Multilevel Modeling" , in p.87 below equation (3) , ...
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16 views

Repeated measures mixed model with nested data

I have been trying to figure out how to run the stats I need for this study for weeks and despite reading endless amounts of information am not much the wiser! If anyone can help, I would be hugely ...
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2answers
70 views

How to simulate a random slope model

I would like do create a mixed linear model for an unbalanced dataset (different number of events per subject and a few missing values for some time points). I am using ...
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0answers
9 views

Hypothesis testing in GLMMs - How to set up sequential LRTs

I'm fitting a generalized linear mixed effects model to my data. I have three fixed effects, and one random effect nested within one of the three fixed effects. The response variable is a count, ...
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1answer
29 views

How to compute MSE of linear mixed model

Considering the linear mixed model, $y=X\beta+Zb+e$. After parameter estimation, we want to compute the MSE of the model. First, we compute the BLUP of b. Then $MSE = ||y-X\beta^*-Zb^*||^2$. Is the ...
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31 views

Modelling against “day” or “day^2” in to look at change over time?

I'm a masters student trying to model changes in behaviour, heart rate variation and faecal cortisol as welfare measures in sheep over the course of 22 days. Days -4 to -1 is used as baseline, day 0 ...
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10 views

3 categorical variables (2 are repeated measure variables) and 1 continuous variable - what analysis?

I originally ran a 2(inclusionary condition)x2(interaction with close other vs stranger)x2(time of pain measurement-repeated variable) mixed manova with 2 dependent variables(physical pain ...
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1answer
31 views

linear regression vs linear mixed effect model coefficients

It is my understanding that linear regression models and linear mixed effect regression models will produce the same regression coefficients (i.e., fixed effects); however, linear regression models ...
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43 views

How can I test variance explained by the factor group if each subject in the group comprises a different number of measurements?

The data structure I have 2 groups with 30 subjects each. Each subject has a different number of fibers (approximately 46000 +/- 3000) of different length (see histogram). My goal is to determine how ...
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2answers
34 views

Testing the variance component in a mixed effects model

Say $y=X\beta+ Zu +\epsilon$ is our mixed effects model where $u=(u_1,..,u_r)$ and $u_{j} \stackrel{i.i.d.}{\sim} N(0, \sigma^2_{a})$ for $j=1,...,r$ and $\epsilon=(\epsilon_1,...,\epsilon_n)$ are ...
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3answers
64 views

Estimates of the variance of the variance component of a mixed effects model

Say $y=X\beta+ Zu +\epsilon$ is our mixed effects model where $u=(u_1,..,u_r)$ and $u_{j} \stackrel{i.i.d.}{\sim} N(0, \sigma^2_{a})$ for $j=1,...,r$ and $\epsilon=(\epsilon_1,...,\epsilon_n)$ are ...
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8 views

SPSS MIXED: Getting estimated marginal means for repeated measures

Any advice for getting estimated marginal means with a within-subject variable? I am looking at the dependent variable SIR over three time points (pre, mid, and posttreatment). My syntax is: ...
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20 views

Is it statistically admissible to run multiple iterations of the same model but change the base level factor in order to get specific comparisons?

I have an agricultural experiment in which I was interested in seeing how parental identity of dam and sire impacted the number of buds formed and the resulting number of buds that survived ...
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43 views

List of nlme models

I am trying to find a list of models that nlme provides. I am completely new to this area and finding it hard to get a comprehensive list of models that nlme provides facilities for. I have tried to ...
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20 views

Mixed effects model for repeated measures to test for factors that are either constant or dynamic within an individual over time

I am dealing with a rather complicated dataset with repeated measures of the same individuals at various time points (samples were collected at different time points and different number of samples ...
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44 views

How can I extract a residual variance-covariance matrix in lme?

I have been using MCMCglmm in R to fit bivariate (two response traits) mixed models in R, but now I need to move to lme to account for temporal autocorrelation of the residuals. In MCMCglmm I can fit ...
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9 views

Longitudinal data with different response measurement types

I intend to fit a generalized linear (possibly mixed) model to longitudinal count data. However, I am running into an issue. The response I am modeling is a measure of student activity involvement. At ...
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48 views

T tests on proportions - Wrong, but how wrong?

In psychology, and probably a number of other disciplines, it's common practice to test between-groups effects on a binary variable, such as accuracy, by aggregating data within participants, and then ...
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1answer
73 views

Difficulties obtaining valid predictions when using interactions

I examine long term trends (2003 to 2014) for a continuous dependent variable. I want to predict the mean each year in relation to income category. Income is arranged in quintiles, from 1 (poorest) to ...
3
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1answer
58 views

Why should one use EM vs. say, Gradient Descent with MLE?

Mathematically, it's often seen that expressions and algorithms for Expectation Maximization (EM) are often simpler for mixed models, yet it seems that almost everything (if not everything) that can ...
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7 views
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21 views

Mixed effects model with autocorrelation between fixed and random effects

I have never posted here before, so apologies if I do not follow the correct format. My experiment design is I have 12 reps each of 4 different species of plant which I experimented on in 2 blocks, ...
3
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36 views

The use of the negative binomial dispersion parameter in model selection…?

I'm doing model selection, analysing the effect of a number of variables on the number of shoots browsed by deer, using the number of shoots available as an offset variable. My data distribution is ...
2
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1answer
27 views

Mixed Effects Analysis in MATLAB

I am new to Mixed Effects analysis, so please forgive my ignorance. I would like to determine if there is any significance between the means of two successive time points in an imaging ROI study. Each ...
2
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0answers
20 views

Interpreting interaction between time and time-varying predictor in mixed models

I have measured the DV and predictor at 2 timepoints in a single group, and am using the MIXED procedure in SPSS. I want to see whether change in the DV over time is predicted by change in the ...
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0answers
15 views

Non-nested model with uniquely identifying groups

I'm testing various specifications of linear mixed effects models with lmer() in R. The data are fiscal year firm-level, so ...
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3answers
45 views

Multilevel modeling for limited dependent variable

I am doing the research, using Multilevel modeling, with limited dependent variable number of days- it is limited downward (0) and upward (30). Is it necesarry to use Multilevel logit model? Or is it ...
5
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1answer
76 views

Are group effects in a mixed effects model assumed to have been picked from a normal distribution?

Say we're interested in how student exam grades are affected by the number of hours that those students study. We sample students from several different schools. We run the following mixed effects ...
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0answers
43 views

Testing for effect of covariate in nonlinear mixed model, T-test or F-test?

I am using package nlme for nonlinear mixed model. I use SSlogis self-starting model( Bates Pinheiro, 2000) for my model. ...
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10 views

What's the drawback of using interaction terms to analyze the pre-post control data?

I am trying to analyze the data with the pre-post-control design in the context of RNA-seq analysis. I have read Best practice when analyzing pre-post treatment-control designs, but I am still ...
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2answers
44 views

Does this mixed model violate assumptions of independence?

A disturbance event caused damage to 5 streams (Set1). To quantify this damage, five additional unimpacted streams (Set2) were picked for comparison. During the selection process every effort was ...
3
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1answer
90 views

Repeated-measures linear mixed effect model

I have used a repeated-measures ANOVA in SPSS to analyse some of my data. It's the typical approach in my area, but I think it might be more appropriate to use a mixed effect model. However, I ...
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2answers
22 views

Variance for Mixed Linear Model

In this mixed linear model(LMM) y is our response variable, XB is our fixed effects Matrix and Coefficient, Wu is our random effects matrix and coefficient and E is our error term with variance y for ...
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9 views

How do I get estimates for a specific time point in a linear mixed-effect model (using R)?

I have an experiment using a number of mice. I measure something (lactate) over 4 time points. Using the nlme library in R, I analyze the data with the following model: ...
3
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1answer
218 views

Model Matrices for Mixed Effects Models

In the lmer function within lme4 in R there is a call for constructing a model matrix of ...
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0answers
11 views

Conflicting Mean Squares, lme vs. lmer

thanks in advance for the help. I've been getting different values for the mean squares (and as a result, F-values) using the base R lmversus ...