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

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25 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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0answers
27 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
8 views

difference between regression model and design model [closed]

how can we differentiate between regresssion model and design experiment model ?? And what is the critaria to set the alpha value in central composite designs ??
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0answers
23 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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0answers
20 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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0answers
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, ...
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3 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 ...
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0answers
17 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 ...
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0answers
11 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 ...
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1answer
31 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 ...
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0answers
15 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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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 ...
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0answers
13 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 ...
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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 ...
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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 ...
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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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0answers
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 ...
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1answer
13 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 $i$). ...
1
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1answer
51 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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0answers
5 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
57 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
147 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 ...
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0answers
12 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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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 ...
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1answer
119 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
34 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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4 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
71 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
55 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
38 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
72 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
52 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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33 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. ...
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2answers
163 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: ...
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1answer
40 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
23 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 $e_{ij}$ ...
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0answers
25 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 ...
0
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1answer
30 views

Understand mixed models SPSS [duplicate]

On a mixed model on SPSS I got the following results: in the table called "Type III Tests of Fixed Effectsa" ...
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0answers
21 views

Meta analysis on multiple endpoints and unknown covariance

I am doing meta-analysis on intervention studies on human subjects where a number of measures were obtained before and after the intervention in a treatment and a control group. We categorize the ...
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0answers
21 views

Linear mixed models

I have some spatial measurement for two quantities, x and y. y is my dependent variable that I am looking to build a linear mixed effects model.Each point in space (lat,long) has one value of x, for ...
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0answers
22 views

Is this interpretation of mixed ordinal logistic regression correct?

I am doing mixed ordinal logistic regression using clmm function in ordinal package. Before running the clmm model I have changed my DV into ordinal variable using: ...
0
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0answers
27 views

Auto-correlation vs. number of observation periods

I've just read an excellent post mix model I've a question connected to that. Roland, can you recommend any reference to a comment that if one have not enough observation periods then it is ...
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0answers
18 views

Is there any possible method to calculate effect size in SPSS mixed model?

I run MIXED command for mixed model analysis of repeated measured data. However, there is no option or menu for estimate power(like partial eta in GLM) in mixed analysis. Is there any method to ...
0
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1answer
38 views

Modeling error structure in lmer in R?

Is it possible to add a parameter to lmer model which will be modeling the error structure? Sth similar to TOEP(X) and SP(POW) from SAS???
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0answers
15 views

Confidence intervals for multinomial mixed models

I am using the ordinal package in R to create a multinomial mixed model using the clmm2 function. However, I cannot find a way to get confidence intervals for the coefficients; confint() does not work ...
3
votes
2answers
147 views

Do the residual plot and QQ plot look normal?

I am doing linear mixed model and would like to check the assumptions using residual plot and QQ plot. Here is my code: ...