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

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2
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1answer
24 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
votes
1answer
44 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 ...
1
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0answers
6 views
0
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0answers
5 views

Specifying a Covariance Matrix in R [on hold]

Currently, I have a mixed effect model problem that looks a bit like this Y=μ+X_j β+α+ε With Y as the test statistic, μ is the scalar mean, and x_j(nx1) is the marker with scalar coefficient β (In ...
2
votes
0answers
17 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
votes
0answers
27 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
votes
1answer
20 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
8 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 ...
1
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0answers
10 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 ...
1
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3answers
40 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
votes
1answer
66 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 ...
0
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0answers
33 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. ...
1
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0answers
9 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 ...
1
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2answers
40 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
votes
1answer
74 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 ...
1
vote
2answers
21 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 ...
0
votes
0answers
8 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: ...
1
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0answers
18 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 ...
1
vote
0answers
10 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 ...
1
vote
0answers
9 views

Showing shrinkage with a plot for the interaction coefficient in a mixed-model

I am trying to illustrate shrinkage in linear mixed models in a 2x2 factorial design. I would like to show the shrinkage effect for all coefficients including the ...
0
votes
0answers
8 views

How to analyze the following cross-over design?

In a pilot experiment I'am running, we use a counterbalanced crossover design, consisting of 2 experimental conditions and one control condition. (In total 6 orders (3x2x1 = 6) Due to time constraints ...
0
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0answers
8 views

Structural zero design in mixed effects model

I would like to do a mixed effects regression that is like this: ISI ~ Location + Stage + Stage*Location + 1|Patient/Chan Where Location and Stage are fixed ...
1
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0answers
24 views

Spherical Parameterization of Variance-Covariance Matrix in Mixed-Effects Regression

I wonder if someone can please help me with a passage on the article by José Pinheiro and Douglas Bates on unconstrained matrix parametrization. I have been slowly working through it, and getting ...
0
votes
0answers
11 views

Conditioning on random effects?

To protect the innocent, I'm going to fabricate an example. Suppose I've got 100 musicians: 50 attended school A, 50 attended school B. I'm interested in determining which school tends to produce ...
1
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2answers
25 views

Overall significance of multiple downward trends?

I am uncertain how to formally establish that I observe a negative relationship between X and Y in multiple sets of linked data points. I have analyzed several cells in which values of interest (Y) ...
0
votes
1answer
57 views

Case-control Matched Clustering in Generalized Estimation Equation (GEE) (R:geeglm)

Question: I have matched case-control data and I would like to take advantage of that in my GEE analysis. In the standard approach to GEE analysis, we call each subject a cluster and fit ...
0
votes
0answers
11 views

Why SAS gives more denom DF in type3 test to subject level covariates than time in linear mixed models

I was working on a longitudinal data data set which had information about 59 patients and their psychological test scores measured at 5 different time intervals. I used Containment method type of ...
1
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0answers
13 views

Distinction between fixed effects and random effects for continuous predictors

The distinction between fixed effects and random effects seems intuitively clear to me. A factor is a fixed effect if the set of possible levels for the factors is fixed. A fixed effect factor would ...
1
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0answers
13 views

Help with repeated measures analysis in a complex design

I'm looking at a study measuring blood flow in the brain, there are 8 subjects in this study, with 18 measurements each. The measurements are done 6 at a time in three different time points ...
0
votes
0answers
10 views

Anova Error term complexity unnecessary?

There is often confusion about properly using Error term in anova. However, following example show that the output remains the same whether it is a simple entry of Error(subject) or more complex ones. ...
0
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0answers
27 views

Mixed-effects in SAS

I am analyzing weekly data on 50 products which were sold in a number of shops during one year. My goal is to estimate a mixed-effects model for unit sales with heterogenous AR(1) error structure. ...
0
votes
0answers
6 views

interpreting random slopes in saturated mean model

When building a linear mixed model, it is often recommended to first model the covariance model, after which one builds the mean model. For building the covariance model, often one starts by ...
1
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0answers
17 views

What is the “variance component parameter” in mixed effect model?

On page 12 of Bates' book on mixed effect model, he describes the model as follows: Near the end of the screenshot, he mentions the relative covariance factor $\Lambda_{\theta}$, depending on ...
0
votes
0answers
12 views

Mixed Linear Model - REML approach AI or FS algorithm

I am trying to see if there is a situation where Fisher scoring algorithm would be better than Average Information algorithm. I know that Average information algorithm is more efficient for large data ...
0
votes
0answers
10 views

Performing Interaction Contrasts on mixed-models in R

I need to run interaction contrasts on the following data set. It is a mixed design with the dependent variable a questionnaire score measured across five test days (within-subjects variable 'Day'). ...
0
votes
0answers
30 views

lme4 variance of predictions

I want to calculate standard errors of predicted outcomes from a mixed-effects model estimated via lme4's glmer function. Since my question is quite basic, I use a sloppy notation and hope that it ...
2
votes
2answers
91 views

GLM with multiple imputation or mixed model

I have a data set with repeated measures with two treatment groups where each subject is measured at 3 time points.But the data set includes missing data. In SPSS if I use ...
0
votes
0answers
5 views

Formulation in mixed model

A have a doubts. A don´t write a mixed model considering a time continuous. My problem is the rating of a mixed model whose experimental treatment has seven levels (seven different treatments) and ...
1
vote
1answer
32 views

Negative BLUP in Linear Poisson Mixed Model

For school, I'm tasked with investigating the effect of beta carotene on the prevention of skin cancer. For this, I have data on several patients that are examined over the course of 5 years in ...
0
votes
0answers
16 views

How to define random effects for nested LMM

I investigated the behaviour of 125 individuals in 25 groups of 5 individuals across 4 days. The data is structured as follows (only showing 2 dummy groups and 2 individuals in each group): ...
1
vote
1answer
36 views

AR(1) working correlation matrix with GEE

I'm attempting to fit a GEE model and I have a question about using the AR(1) working correlation matrix. I've read some conflicting information about this correlation matrix. In some books and ...
0
votes
0answers
15 views

Marginal Likelihood of a Non-Linear Mixed Effects Model

The marginal likelihood of a non-linear mixed effects model does not admit a closed-form expression, unless data is normally distributed... or so I was told. Does anyone know of any literature, ...
1
vote
0answers
58 views

Linear Mixed model with lmer in R. How to formulate the within subject factors?

I would like to know which of these formulas is better for answering my research questions (see below) and explain why, or maybe someone can suggest me another one. ...
1
vote
1answer
56 views

R, Pairwise comparison of random variable in mixed model

We measured temperatures of a pond repeatedly every day at each hour for a month at two different depths (i.e., top and bottom). We want to see if the temperatures at the top of the pond are ...
0
votes
1answer
22 views

Deriving mean of percentages from clustered data

I am getting into a roadblock about how to analyse this data set. I hope folks here will be able to give me some hints and suggestions. Here is an example of the data: I'm using sugar as the ...
2
votes
0answers
25 views

Correlated slopes and intercepts in lme4

I have what I think is a simple question. I have run a simple linear mixed model using lme4. It is a random slopes and intercepts model and I am looking at how these intercepts (B0) and slopes (B1) ...
0
votes
0answers
25 views

Repeated measures: Relation between baseline adjusted ordinary regression and random intercept model

I'm currently trying to familiarize myself with linear mixed models (with normally distributed continuous outcome, no generalized versions for the time being). One particular question I'm currently ...
1
vote
0answers
23 views

How to treat different (multiple) measurements on the same subject over time?

Let's say I am interested in some microscopic measurements on a subject, for example, the pore sizes on my hand. I want to see how putting my hand under a humidifier changes the pore size over time, ...
0
votes
0answers
44 views

lme4: Why won't lsmeans output my fixed effects?

I'm trying to plot confidence intervals for linear mixed effects models trained with lme4 and lmerTest in R. I am using this data file, which I've shared via Google Drive. Here is my trained model. ...
3
votes
1answer
29 views

different results from lme and lmer function

I am fitting a random slope and random intercept model using R. I used both lme and lmer funciton for the same model. However I got different results as shown below (different variance component ...