"Mixed models" refers to a class of models developed to account for correlation that may occur within nested data.
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Multivariate linear mixed model in R
I have run into a problem with respect to an application of linear mixed effects model using lme4 package and I wondered if I could seek your help.
This is my model in a multivariate setup where ...
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Simple Mixed Model with 1 Fixed and 1 Random Effect
I have various datasets I need to analyse regarding soil properties, all in the same fashion, with one fixed effect (which is a position along a transect, indicating different land uses). Now my main ...
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How to calculate confidence intervals of $1/\sqrt{x}$-transformed data after running a mixed linear regression in stata?
I have run a series of mixed linear regressions in Stata, some with inverse-square-root ($1/\sqrt{x}$) transformations and others with square root ($\sqrt{x}$) transformations.
How do I calculate ...
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Subject specific vs population average predictions
I am in doubt whether in my thesis I should report on the subject specific predictions of the probability to respond with an 'I don't know' answer, or the population average. Consider for example the ...
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Specifying a correct full model for an unbalanced repeated measures design in R lme4
Recently, I have done a fairly complex experiment, and I am having trouble coming up with a model that is suitable for the data. I have spent a few days reading about, e.g., when random effects should ...
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Simulate LMM data with specific error values using R
I have a need to simulate data in R using the following:
Simulate data for 5 (or more) subjects, indexed by $i$, $(i=1,~...,~5)$ with $6$ observations per subject indexed by $t$ $(t=1,~2,~...,~6)$. ...
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Visualising mixed effects factorial design results
My model is a mixed, multi-factorial one. I am using lme (library nlme) because I also need to include weights to account for heteroscedasticity. I would like to be able to visualize the model ...
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48 views
Stepwise introduction of predictors to mixed-effects models
As the title says, what I'd like to do is stepwise introduction of predictor variables to a mixed-effects model. I'm going to first say what I'd be doing if it were stepwise linear regression, just to ...
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What does the residual higher level variance tell me?
I have a multilevel logistic regression model predicting the probability of item nonresponse, where the random intercept variance at country level takes on the following distribution for the different ...
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1answer
39 views
Mixed-effects model for MZ twin data: avoiding overparametrization
I'm trying to fit a (simple) linear regression using MZ twin data. The reason why mixed-effects are used here is just to correct for correlated responses from the twins.
The current model looks like ...
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46 views
Which ANOVA is most appropriate?
So, I have a question for a proposal and I'm fairly certain I'm getting an incorrect answer from our local "stats guy". For the record, it's archival data so I can't change the items (which aren't ...
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47 views
EM algorithm for Gaussian mix
Can anyone help me with the R code to implement EM algorithm. I got different value if I chose different starting value; clearly this is not good. And the value of $\mu$, $\sigma$ goes to NA after ...
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1answer
30 views
What does the change in intercept mean if you allow for clustering in your data?
When I estimate a logistic binomial regression with an allowed to vary effect on a second and a third level, the overall intercept represents the average log-odds for any level one unit in any higher ...
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A good primer on how people deal with cluster-wise autocorrelation in mixed models?
The courses that I've taken have been primarily in the economics department, but I've been learning more of stats more broadly recently. One thing that I don't understand well is how exactly people ...
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33 views
How do I set up a multivariate hierarchical multiple linear regression in R?
I have two continuous DVs (measurements taken on individual fish), one continuous individual level IV (fish's size), and two site-level IVs (PC1 and PC4). Sites are either take or no take. There are ...
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1answer
66 views
Prediction on mixed effect models: what to do with random effects?
Let's consider this hypothetical dataset:
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1answer
63 views
“ random effects must be less than the number of observations” error in lmer package
I'm trying to implement a regression model with both fixed and random effects. The package I use is the lme4.
I want to find the relationship between the ...
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1answer
35 views
Quantify strength of association of two continuous variables while controlling for random effects
I have a data set from a repeated measures experimental design with different sets of stimuli. I want to know how strong the association between the continuous dependent variable and the continuous ...
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Book on Repeated Measure Analysis
Can anyone recommend a good book or some other reading materials
on repeated measure analysis using mixed model.Thanks.
Hanna
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Bounded response variable [-1;1] - Should I transform it?
I am planning to use two response variables. One is bounded between 0 and 1, and I guess I can use a binomial (or related) error structure. The second variable is bounded between -1 and 1. I am not ...
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2answers
68 views
How do I setup a model with hierarchical structure using lmer in R?
I am trying to isolate the important predictors for my response variable "Y". I know that "TL" (which is an individual level predictor) affects "Y", and now I want to determine if adding the site ...
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Mixed-effect modeling with paired observations & bounded response variables
I am quite new in the field of mixed-effect modeling. For a beginner like me, I guess I combine several levels of complication in my analysis: paired observations & bounded response variables. I ...
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1answer
71 views
How is the Df computed in a mixed model?
The following is the output for a mixed model example. The only difference between fm1 and fm2 is the random factor "URBAN", why the df for fm2 is 5 but not 4? Any help would be great.
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Reporting predicted outcome of mixed effects models
I am analyzing some group-randomized longitudinal trial data with three time points using mixed effects model. Some people missed 1-2 time points, and I didn't exclude any cases with missing dependent ...
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1answer
75 views
How do I interpret the 'correlations of fixed effects' in my glmer output?
I have the following output:
...
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Mixed-effects model for a strongly unbalanced design
I am somehow unsure on the best option to analyze these data.
Here is my study case:
The response variable is a morphometric measure, one for each individual.
During 10 years, say 2000-2009, people ...
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46 views
How do I perform a Mixed model analysis on my data in SPSS?
In my thesis I'm trying to discover which factors influence the CSR (corporate social responsibility, GSE_RAW) behavior of companies. Two groups of possible factors ...
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Predicting from the posterior of a random coefficients model
I've got a model that looks like this:
$$Y_{ig} = \left(\beta_{everyone} + \beta_g\right)X_{ig} + Z_{ig}'\gamma + \epsilon_{ig}$$
in R, this is
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46 views
How to calculate 95% CI for a random effect?
The R code "intervals()" gives confidence intervals for fixed effects only in a mixed model.
*Is there a reason why only fixed effects' confidence intervals are provided?
*Is there any way to get ...
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1answer
151 views
Why do coefficients and significance levels change so much in my OLS? Do I need MIXED model instead?
Please consider the following OLS model:
As a rule of thumb, a VIF score of max. 5 is considered acceptable collinearity in most fields. So for the better part I believed this model to be quite ...
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What does it mean to model a random effect on a main effect only when testing interaction?
I'm monitoring groups of individuals all composed of one male only and several females. I want to test if var1 is correlated with ...
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1answer
61 views
How to prove that Manova is a special case of mixed models?
I am writing my master's thesis in quantile multilevel regression.
My professor all of a sudden decided to change the subject of my thesis into something that could be called "quantile multilevel ...
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26 views
Interpreting Outputs From a Generalised Linear Mixed Model
So I am running an experiment on transmission fidelity in humans depending on information type. This works by having chains of 5 people playing a Chinese whispers type game with 4 passages of ...
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minimum number of data points per group of random effect
I am producing a Mixed effects model with Subject as a random effect. There are 80 Subjects most with 2 data points per subject(some have only one). Is 2 data points per group enough? Is it ok that a ...
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Standard Deviation of Random effect is 0?
I have a model with two random effects
> lmer(TotalPayoff~Type+Game+PgvnD*Asym+(1|Subject)+(1|Pairing),REML=FALSE,data=table)-
>m1
each pairing ...
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1answer
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Appropriate distributions for infrequent events with copycats
I know that infrequent events, especially disasters like earthquakes, can often be modeled by the Poisson distribution. I was thinking of recent events like the Boston bombing and the ricin envelope; ...
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2answers
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How can I test whether a random effect is significant?
I am trying to understand when to use a random effect and when it is unnecessary. Ive been told a rule of thumb is if you have 4 or more groups/individuals which I do (15 individual moose). Some of ...
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Interpretation of probabilities from a mixed-model logistic regression
In the following model specification, which is a random intercept 2-level logistic regression:
Would two lower level units ($i$) with the same value of $x_{1ij}$ and within the same higher level ...
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120 views
Mixed models and normally distributed random effects
I am attempting to analyze some data that includes 10 repeated measurements on 10 different samples. This would normally require using mixed models, and I have attempted to model these using ...
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ANCOVA (GLM) versus Mixed Linear Model with covariate measured at both pre- and post-treatment (in SPSS)
I'm trying to analyze a pre/post study with 4 treatment groups. The Dependent Variable, Speed, measures how quickly a person's facial expression reaches peak intensity; this measure is normally ...
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Does Poisson Regression have an error term?
I was just wondering if poisson regression has an error term? Can a poisson regression have random effects and an error term? I am confused about this point. In logistic regression, there is no error ...
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Are interaction plots only useful for fixed effects?
To test whether you want to add an interaction term to your model, is an interaction plot only useful when both effects are fixed. How do you determine whether to add interactions between random ...
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48 views
Models with Nested Effects
I am having difficulty understanding nested effects. Suppose 20 people each are assigned to treatment groups A B C and D. Would it be correct to say that Person is nested within treatment group? So ...
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Mixed model in simple english
Can someone please explain the intuition behind mixed models in a nutshell? Whenever I read explanations, I get overwhelmed by notation and mathematical jargon. Can someone give me a simple example or ...
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How would you write the model?
Suppose you have SAS code as follows. This is from http://www.ats.ucla.edu/stat/sas/faq/anovmix1.htm.
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Degrees of freedom for mixed model
Using data and code the example from http://www.ats.ucla.edu/stat/sas/faq/anovmix1.htm:
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28 views
How can I analyse results from a repeated in repeated measures mixed design in r
I want to investigate performance in a learning test, where my test animals have been submitted to a number of trials within test day over several test days. I want to investigate if there is an ...
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1answer
72 views
How to extract/compute leverage and Cook's distances for linear mixed effects models
Does anyone know how to compute (or extract) leverage and Cook's distances for a mer class object (obtained through lme4 ...
