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

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19 views

Use lmer to test main effects and interaction

I have to solve a problem using a linear mixed model (lmer). Six subjects performed two tests, (test1, ...
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1answer
17 views

Specification of mixed model effects

I have a study design with a between subjects factor (treatment: verum vs placebo) and a within subjects factor (time: before vs after). Subjects were entered into the model as a random effect. So ...
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1answer
52 views

Likelihood ratio tests using ML vs. REML

I am using Mixed effects models (nlme package in R) to choose the model with the best random and fixed effects. I am following the procedure of Zurr et al. (2009) ...
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15 views

How to test for interactions of continuous measure with two repeated-measures factors in R?

I am doing an items analysis of difficulty ratings of a large set of math problems which were constructed to represent the factorial combinations of two binary factors, feature1 and feature2. The ...
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1answer
24 views

SAS NLMIXED proc and LOGISTIC proc results different

Consider a dataset $Z$ with $S\in \{0,1\}$ as binary response variable and 2 predictors $\{x_1, x_2\}$. ...
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70 views

Assessing the need for random effects terms

During the model selection phase for mixed models, there are typically several possibilities to choose from; in fact, the number of possibilities is increasing in the number of covariates used. How ...
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16 views

Proper Model Selection Randomized Block with Count Data

I have a data set on insect counts that looks like this: ...
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1answer
56 views

Model Assumptions: LMER / GLMER Model where Dependent Variable is a Percentage

I am attempting to build a model for the following dataset: Level 1 Observations (Product-Level): 89000 Level 2 Observations ("BU_SBU" Department-Level): 135 Unfortunately I cannot share a sample of ...
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14 views

Boostrap confidence interval mixed model

I have have about 1000 data points (x,y,z). I am fitting a mixed model to the data, using lmer in R model = lmer(z ~ x + I(x^2) + (1|y)) I am interested in ...
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22 views

Comparing Binomial Success Parameters in a Stratified Approach - An Example in Biostatistics

I would like to contrast the effectiveness of drug treatment and surgical treatment in a study with the following data. Each row represents one trial, and each trial uses either drugs or surgeries to ...
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32 views

Marginal and Conditional $R^2$ for GLMM

I am trying to calculate $R^2$ (variance explained) for a set of data using GLMM's, and . Here's some dummy data. ...
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22 views

Reverse-engineering a (custom goods) pricing algorithm - each db row has: | 3 factors | 2 co-variates | price | (I have over 100k rows of data) [closed]

just wanted to mention up front that my question doesn't concern dynamic pricing, price optimization, revenue management, etc. No time series analysis either. It's just a simple multivariable ...
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1answer
30 views

Controlling nuisance covariate in lmer

I want to control for a nuisance covariate in a linear model. Since the covariate interacts significantly with one of the fixed factors, the homogeneity of regression slopes assumption is violated for ...
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1answer
41 views

Estimates of random effects in binomial model (lme4)

I'm simulating Bernoulli trials with a random $\text{logit}\, \theta \sim {\cal N}(\text{logit}\, \theta_0, 1^2)$ between groups and then I fit the corresponding model with the ...
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23 views

Optimal model/statistical test for my design?

I have a design with 1 between-subject factor and 2 within-subject factors as independent variables and 5 dependent variables (longitudinal accelartion, lateral acc., response time, first conscious ...
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9 views

Group mean centering predictors for crossed random effects

I'm fitting a mixed-effects model, in which I wish to test the effect of $X$ on $Y$, with crossed random intercepts and slopes for each subjects $S%$, and for each level of an additional grouping ...
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45 views

Model averaging predictions from lmer models

I am trying to model average predictions (not betas) and estimate confidence intervals from linear mixed models run with lme4::lmer. I have experimented with functions in the MuMIn and AICcmodavg ...
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61 views

How can the R-matrix in a mixed model be estimated?

In Henderson's Mixed Model equation: $y = X\beta + Zv + \epsilon$ where the joint variance of v and the error term is: $Var\begin{bmatrix} v \\ \epsilon \end{bmatrix} = \begin{bmatrix} G & ...
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73 views

How to report results from a linear mixed model “test of fixed effects” in SPSS?

What is the appropriate way to report results for linear mixed model based on the "test of fixed effects" table in SPSS? Is it just (F=xxx, p=xxx)? This isn't my data but this is an image I found of ...
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30 views

Comparing mixed-effects and fixed-effects models

Given three variables, y and x, which are positive continuous, and z, which is categorical, ...
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6 views

repeated measures mixed model with different number of measure per group

I have a an experiment with 3 groups. Two of these groups have the outcome of interest measured at baseline, 3 months and 12 months and one group has only been measured at baseline and 12 months. My ...
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36 views

Comparing different methods of discrete-time survival analysis

I'm investigating a discrete time survival problem (the units are months and exit times range from month 1 to 36). From looking around so far, it seems like there are a few different types of model ...
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17 views

Weighted Mixed model

I am trying to fit a standard mixed model to my data using lmer in R. I have both fixed and random effects. My fixed effect factor is say x, and my dependent variable is y I would like to make my ...
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1answer
30 views

What is the best approach for this set-up: RM ANOVA / MANOVA / Mixed-Models?

I have a simple dataset from a within-subject design. Each participant provided a verbal description of 3 stimuli. The descriptions were coded so that they consist from objects each belonging to 1 out ...
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8 views

Comparing trajectories of two outcome variables in longitudinal data

this is the situation: Study-type: prospective population-based (N = 4,000) with baseline (T1) and three follow-ups (T2 - T4) Between variable: cardiovascular health at T1 (good vs. poor) Within ...
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8 views

Model Selection In small clusters

I have a question please. Is ok to make model selection with MLE in small cluster in order to allow for comparison, and after getting the final model then fit the final model with REML? Since REML is ...
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12 views

How to include questionnaire data with behavioral counts in lmer() maximal logistic regression model?

I’m using a maximal logistic regression model to analyze some data. I would like to keep using this technique if possible, just include more data in the model. The main data I’m looking at is counts ...
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11 views

non-uniform residuals in repeated measures mixed model; larger residuals further in time

I am analysing data from a longitudinal study in SAS and see time-dependent patterns in the residuals. Subjects in four groups (A to D) were given a treatment at time=0; and continuous response ...
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10 views

Is GzLMM with linear linking function identical to (G)LMM?

Should I hesitate to report a "generalized linear mixed model with linear linking function (and assumption of a normally distributed target)" as simply a "(general) linear mixed model" in a ...
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2answers
61 views

Mixed Model Type-III Sums of Squares- R vs SPSS

The age old question of comparing sums of squares (SS) between programs has reared its ugly head again. I am trying to replicate output in SPSS, that was computed using Type 3 Sums of Squares, in R. ...
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17 views

Degrees of Freedom using “Containment” method

I have a question about the way SAS uses the "containment" method to obtain degrees of freedom in mixed models. In particular, I think SAS does the wrong thing in obtaining df for least-squares means ...
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1answer
82 views

Examining trends with interactions and with stratification - obtaining discordant results

I'm examining the effect of income (categorized into quintiles) on a response variable during different years (from 2003 to 2014). I adjust for some other covariates and have repeated measurements on ...
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6 views

Removing contrast effect in mixed modelling deletion test

I am doing a mixed, linear regression analysis and now want to conduct a series of deletion tests on my max model, where I test if there is a significant increase in deviance once an effect that binds ...
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1answer
40 views

Advantages of counterbalancing vs. randomizing stimuli

I'm designing an experiment, in which 40 participants answer 10 questions, 5 in condition $A$ and 5 in condition $B$, and I'm interested in the difference between the two conditions. It's not clear ...
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23 views

Treatment of mixed effect models for Box-Cox transformation

To analyse the Box-Cox transformation in a mixed effect model, no simple transformation/ code in R exists. So which of the following approaches would be valid ways and why? 1) Take a random sample ...
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16 views

Zero-inflated mixed models with two-stage fitting

Zero-inflated models have a count component (Poisson/Neg. Binomial) and a zero component (logistic regression part). glmmADMB supports the zero-inflation feature but only through estimating a ...
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2answers
69 views

Random intercept turns insignificant - Interpretation

I am running a intercept model with intercepts varying across people in R. My independent variables are all numeric variables. My question is a general one: I saw already that it can happen that my ...
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31 views

Box cox for mixed models in R

Consider a mixed model generated using the lme function in R. How can I consider the Box-cox transformations of this model in R? I have seen similar questions being asked before but they did not give ...
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6 views

Error appears for kml function in Latent Growth Mixture Modelling

I am trying to run the kml function for a simple dataset with $n=59$ and body weight measured at $8$ time points. The commands used were: ...
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1answer
20 views

Addressing a mixed design analysis of variance when only one of the two groups went under repeated measures?

so essentially I have 2 groups (A and B, A is a control, and B can be referred to the "expert" group), and group B went under a specific training program (two times points, one prior to the training, ...
3
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1answer
152 views

R glmer.nb output. How to get $\hat{\theta}$?

I would like to obtain estimated $\theta$ from glmer.nb function in lme4 package. In my understanding this function fits the model: $$ Y_{ij}|\boldsymbol{B}_{i}=\boldsymbol{b}_i \overset{ind.}{\sim} ...
2
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1answer
44 views

multiple imputation of longitudinal, time-unstructured data

I have a longitudinal dataset of radiation exposures of an occupational cohort. A percentage of the exposure values are missing and I would like to multiply impute the missing values (it is one option ...
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27 views

In the optimal model, do I need to change 'REML=FALSE' to 'REML=TRUE'?

I did the model comparison using these three models: ...
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12 views

Can you compare groups over time if data has been collected at different time points?

If have two groups with follow-up measures of a normally-distributed continues outcome measure. One group is measured at 4 time points with unequal intervals. The other group is measured at 7 time ...
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7 views

effect of accounting clustering

I am analyzing a data where measurements are taken at pups and these pups are nested to their corresponding mom (rats). When I accounted for clustering, factors diet, drug, and interaction of diet ...
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70 views

Problems fitting a repeated measures model (time series analysis): fixed-effect model matrix is rank deficient so dropping 1 column / coefficient

I’m trying to fit a model with 4 parameters by not including all the interactions, just including the interaction which got biological sense. This is my data ...
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28 views

Syntax for a logistic multilevel analysis in R?

I am looking for advice on what package and syntax to use in R for modelling a logistic multilevel analysis with variables as follows: Dependent variable (binary) = 0 or 1 Independent variable 1 ...
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0answers
12 views

How to include replicates in linear mixed models in SPSS?

In my study I had 11 radiocollared hares which i gave 3 different treatments. one treatment was the release of stressed hare sounds in combi with red fox sounds, the second treatment was sheepsound ...
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1answer
25 views

Mixed model analysis: random vs repeated statement

I have data from a longitudinal parallel groups study where there are 46 subjects randomized to 1 of 5 treatment groups, each subject with roughly 13 observations over time on a given outcome measure. ...
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20 views

How many random effects to specify in glmmADMB?

I am not sure if I could use 4 random effects in a glmmADMB model. According to Bolker et al. (TREE 24: 127-131, 2009) when there are more than 3 random effects MCMC should be used. However, I do not ...