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

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Checking assumptions of a mixed model

I was wondering how to check the assumptions of a mixed model in R. Suppose I fitted a model with lmer. Is this what I should do? ...
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16 views

Significant cross-level interaction despite lack of variance in level-1 slopes

I have a logistic HLM model with one level-1 predictor and without level-2 predictors. Random variance components are significant for intercepts, but far from significant (p>.5) for slopes. In my ...
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29 views

Model formulation of mixed models: from R (nlme and gamm) syntax to mathematical

I have finalized two types of models, a linear mixed effects model and a generalized additive model for my data set. I have read and understood how it works and how to choose which model would be the ...
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7 views

How to interpret change in intercept when a random effect is added to a mixed model

I have a fixed effect model, constructed in SAS using Proc Mixed as: proc mixed data= etc...; model ca = p t s /solution; run; which yields the following ...
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24 views

Subject-specific graphics for repeated-measure design

I am doing linear mixed effect modelling testing the effect of treatment on pitch, with ...
1
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0answers
113 views
+50

Obtaining adjusted proportions with lme4, using the glmer-function

I aim to estimate the annual proportion of patients (% of patients) that are smokers in a population whose age and sex must be taken into account. In other words, I want to calculate the adjusted ...
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9 views

temporal pseudoreplication in testing possible combinations in logistic model [closed]

I am interested in comparing mortality of animals when they are put in groups of a fixed size but of varying composition. Suppose I have 9 different genetic lines and I form the following categories: ...
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0answers
13 views

Correct df in longitudinal linear mixed model?

I am having trouble understanding how to correctly apply a linear mixed model to my data to measure the effect of wifi exposure. 4 beehives contained sensors collecting data on temperature (DHT22_t, ...
2
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1answer
35 views

Mixed effect modelling with multiple, nested random variable

Goal: comparing pitch (Hz) on three types of words Dependent variable: Hz Fixed predictor variable: word-type, points (measurements taken from five points on each token, to capture Hz change within ...
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26 views

what is the meaning and purpose of modeling a data?

Background: I collected a whole years access logs of my website, counted visit frequency for every user, and the numbers of user at each unique frequency, I got a distribution: $n_w \tilde\ D_w(f_w ; ...
2
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28 views

Multiple comparisons for variance structure in R lme fit

How can I compare variances for different levels of a factor in a mixed effect model? I'm fitting a mixed effects model (in R using the ...
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0answers
26 views

Comparison of crossed random effects (mixed models): lmer vs. MCMCglmm

I read that lmer can handle independent (often labeled as crossed) random effects in mixed models. It seems to be possible with MCMCglmm as long as groups for the random effects are uniquely labeled. ...
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21 views

How to analyze data with DV only measured at the group level and moderator measured at the individual level?

This may be a relatively simpleton kind of question to ask, as this forum seems to be rather statistically sophisticated, but I'm rather mixed up right now. I ran a study that involved individuals ...
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11 views

How to summarize a series of cumulative variables and extract their contributions to the variation explained by the summarized variable?

I want to use a mixed logistic regression. My explanatory variables are ten variables corresponding to cumulative variables measuring the same value over the 10 years preceding the year of interest, ...
0
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0answers
5 views

Extracting random variable coefficients from model averaged objects

I'd like to extract the coefficients of the random effects from a model averaged object of class averaging created in the package ...
0
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0answers
22 views

unbalanced groups in mixed design ANOVA

I want to perform a mixed design ANOVA. Time is the within subjects factor and the between subjects factor is Borderline, which is a categorical variable (borderline yes or no). There are 30 people ...
1
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0answers
12 views

Poisson regression with underdispersed and truncuated/censored upper bound

I'm analysing data from an experiment in which participants, over a number of trials, were presented with 8 boxes - 7 containing gold coins, and 1 containing a pirate. Their task was to open as many ...
2
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1answer
38 views

Interpret effect of adding random effects to ordinal regression (R - ordinal package - clmm)

I know there are already lots of questions around this topic (especially this one and this one) but I haven't really seen anything that directly helps me (It will be obvious I'm not a great ...
1
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1answer
22 views

ANOVA, mixed model, or something else, for ordinal groups with a continuous outcome?

Possibly a simple / daft question so apologies in advance... Suppose I have several independent observations of a continuous variable, like height. The observations are grouped, and I would like to ...
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0answers
4 views

Variance component analysis nlme

Is there a way to carry a variance component analysis using nlme or lme4 packages and how would I calculate the percentage of variance that is attributable to the random effects? For example, my ...
1
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0answers
14 views

How to specify random effects in lmer

I have 3 groups of animals that are divided into 3 subgroups, each subgroup contains animals that are specific to each subgroup (there is no same animal in two groups). How do I specify random effects ...
4
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1answer
21 views

What to do about very unstable mixed-effects models

I'm working on some poisson mixed effects models for an interrupted time series analysis, and I'm running into two frequent errors. The first I've posted on Stack Overflow, as it appears to be purely ...
2
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0answers
14 views

Mixed effect linear model R

Could someone please help me with interpretation of the results I've got using nlme package from R. I have 3 groups of animals, each group is divided into 3 subgroups, and each subgroup has a number ...
0
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0answers
23 views

Combining Model with parent Models

I have created linear models for all present groups in my dataset. Lets say that the grouping is determined by the combination of two nominal variables A & B. A has 5 distinct values and B has 4 ...
2
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30 views

What happens when fixed and random effects overlap?

For example, if your response is the number of ticks on deer, and you sample deer at 10 sites. You include 'site' as a random effect, but you also want to include the density of trees at each site as ...
0
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1answer
20 views

Mixed model (Multilevel) with two INDEPENDENT Random Effects [lmer]

I like to estimate a mixed model with two Random Effects, that are independent of each other and among themselves. I use Panel data with a nested structure (counties $j$ nested within regions $i$). ...
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1answer
56 views

In what sense is the interpretation of coefficients in a GLMM subject-specific?

There is something I'm not quite understanding conceptually about the output from generalized linear mixed models. I have read that the target of inference in GLMMs is subject-specific. For example, ...
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6 views

Question about Pseudo R-squre of mixed logit and likelihood with constant only

I have a question on Pseudo R-squre calculation. Normally, if one wants to calculate R2 manually, R2=1-L0/LL. I'm using mixed logit model.I find that in the results of mixed logit, there isn't ...
3
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1answer
64 views

modelling time as continuous vs. discrete

I am writing an analysis plan for data that is collected on approximately 30 people at approximately 5 unevenly spaced time points. I am planning to analyze the data via a repeated measures mixed ...
5
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1answer
157 views

Default lme4 optimizer requires lots of iterations for high-dimensional data

TL;DR: lme4 optimization appears to be linear in the number of model parameters by default, and is way slower than an equivalent ...
0
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0answers
14 views

Effect of random factor in Mixed effect model

Is there any way to test the effect of a random factor in Mixed Effect Model? I am very unfamiliar with Mixed Effect Model, and my question may sound stupid. I would like to see the effect of a random ...
2
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1answer
49 views

What is the difference between a mixed effect model and a linear regression model?

Can somebody please explain the difference between a mixed model and linear regression analysis? (I have very limited knowledge of statistics.)
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0answers
12 views

How to implement cross-classified(multiple group membership) repeated measure analysis?

Happy new year! I have a longitudinal dataset with 4 time points (2 measured in fall and spring semester of prek year, and 2 in fall and spring semester of k year). As a result, a same student has 2 ...
5
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1answer
125 views

A potential confound in an experiment design

Overview of the question Warning: This question requires a lot of set-up. Please bear with me. A colleague of mine and I are working on an experiment design. The design must work around a large ...
2
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1answer
37 views

Is it better to remove higher order interactions or least significant terms first in model simplification?

I have a mixed effects model with 3 explanatory factors and a full interaction set (including 3 way interaction). This is the full model. Factor 1 is time and I am interested in the change in the ...
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7 views

Parameter Tying: Using observations of one category to lift estimates of baseline ability

I am trying to model an individuals' ability to perform one of several similar tasks. We would like each individual's performance to reflect three factors: the mean ability of the general population, ...
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0answers
5 views

Calculate elasticities of mixed logit

How do we calculate the dis-aggregate direct elasticity of a random-coefficient logit model?
3
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1answer
74 views

Can we model non random factors as random in a multilevel/hierarchical design?

The distinction between strictly random variables (which ought to be modeled as such) and non random variables which some argue could be modeled as random if it is a hierarchical/multilevel model, is ...
2
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1answer
58 views

Interpreting Reaction Time data with mixed-effects model

I have a problem with interpreting Reaction Time results with mixed-effect models. In the experiment, participants were split into 2 conditions. They looked at the same set of pictures and then took ...
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2answers
40 views

Proportion of variance in dependent variable accounted for by predictors in a mixed effects model

Let say I've ran this linear regression: lm_mtcars <- lm(mpg ~ wt + vs, mtcars) I can use anova() to see the amount of ...
2
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1answer
78 views

Mixed models and backward elimination

Let's say I have a data like this, and I'm trying to build a mixed model. ...
0
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0answers
10 views

P-values for random effects when using REML [duplicate]

I'm using JMP to fit a model for an unbalanced split-plot design. Because it's unbalanced, I'm using REML rather than EMS. However, I would like to get test statistics/p-values for some of the random ...
5
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1answer
53 views

Do I need more than one random slope?

When constructing a GLMM in R, do I need more than one random slope if I "see" that slopes differ for multiple continuous variables? In my case, I am analysing the number of plant species (...
2
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0answers
36 views

ANOVA P-value adjustments for semi-continuous data

In tests such as the Bonferroni post-hoc p-value adjustment test, convention is to correct the data with a constant, equivalent to the length (number) of pairwise comparisons that are being performed. ...
9
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2answers
168 views

Random- and fixed-effects structure in linear-mixed models

Consider the following data from a two-way within subjects design: ...
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3answers
43 views

Test for effect of groups in a mixed effects model

This model is a simple linear regression: mtcars_lm <- lm(mpg ~ wt, mtcars) And this model adds cyl as a random effect: ...
1
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1answer
41 views

Mixed models (lme4) + lsmeans to estimate trend in population means

I aim to estimate one populations mean blood pressure during different years. Here is the setting: (1) 7400 onservations; repeated measurements. Unbalanced. (2) measurements are undertaken anually ...
0
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1answer
24 views

Complex level 1 variance mixed effects models in R

Take this mixed effects model in R: $y_i = \beta_0 + \beta_1X_{ij} + u_{j} + e_{ij}$ where $u$ is a random effect (level 2 residual) with groups $j$. It is possible to allow the variance of $e_{ij}$ ...
0
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0answers
27 views

Degrees of freedom for a 3x2 mixed ANOVA

I want to report the results of a 3x2 (system x task) mixed ANOVA. System is a between-subject factor with 3 levels, while task is a within-subject factor with 2 levels. For one of the independent ...