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

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6 views

Correlation fitted-residuals in mixed models

IN OLS linear models, fitted (predicted) and residuals scores are uncorrelated. I was under the impression that the same held true in mixed models. However, I have here an example model where fitted ...
2
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1answer
14 views

conducting multi-level regression on ordinal DVs with imputed data in R

Do you know of an approach/package that facilitates mixed model regression of ordinal dependent variables on multiply imputed datasets in R? Ideally, the function takes: a list of multiply imputed ...
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0answers
10 views

Compare LMM GLMM (generalised linear mixed model, negative binomial) by numerical measure (AIC BIC, cross validation, R² squared) for model validation

How to compare results of generalized linear mixed model (GLMM, negative binomial) with a log transformed linear mixed model (multilevel, hierarchical) . I have a data set (counts), which is nested. ...
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0answers
21 views

R² (squared) from a generalized linear mixed-effects models (GLMM) using a negative binomial distribution

I try to compute the marginal and conditional R² for a GLMM using a negative binomial distribution by following the procedure recommended by Nakagawa & Schielzeth (2013) . Unfortunately, the ...
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1answer
13 views

Calculated breeding values using markers using animal model in R

Animal model (frequently used in animal science and sometime in human or plants) is mixed model with: $y$ = $X$$b$ + $Z$$u$ + $e$ y is observed values for any quantitative variable, $Xb$ is fixed ...
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0answers
16 views

center variable separately for each factor in linear mixed model?

I am working on a relatively simple mixed model where I have two continuous predictors with an interaction term and three sites. I am treating the two predictors as fixed effects and the site as ...
0
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0answers
19 views

Experimental design and mixed models

I want to test effect of 3 PH on larval development. I would like to know what is the best experimental design and statistical analysis. We can only use 3 compartments of sea water, each one with a ...
1
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1answer
39 views

Multivariate model in lme() with independent random effect, similar to MCMCglmm

I would like to specify a multivariate model with lme with a random effect for group which is independent across variables. I found this post, which explains that ...
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0answers
40 views

Mixed effects modelling; what to do when model is over-specified?

I'm trying to use mixed-effects modelling to analyse some data. There are a number of variables that I need to specify within the model, two of which are between-participants (...
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0answers
12 views

Fitting a Mixed Model with Random and Repeated effects in SAS

I have want to fit a linear regression with repeated measures and random effects. The data come from clinical observations. In CT images The dependent variable is the diameter of a lymph node lesion ...
2
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2answers
57 views

What is the right way to analyze a nested design in R?

I know that there are already a host of questions about nested designs but many of them haven't been answered or come from biological domains which I sometimes find hard to transfer to my domain. I ...
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0answers
24 views

Demand Forecasting : Montecarlo Simulation

I am trying to build a demand forecasting model for human resource team. I have thought of using monte carlo simulation method to do it. Is it the right technique for it? Has anyone used it to ...
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0answers
22 views

How to do a power analysis for an unbalanced mixed effects ANOVA?

I need suggestions for how to calculate the $n$ required for 80% and 90% power for >30% change from baseline ($T_0$) at $T_1$ or $T_2$, drug vs. placebo, 2:1 ratio; 20% CV in test; factors: subject, ...
0
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1answer
49 views

How to compare models from different but related datasets?

I'm building regression models on four the different but related data set and at the end, I want to test the significance of models. Since my models are built in a different data set, it's not ...
0
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0answers
28 views

How to model non-linear time courses with nlme

I have some time course data which plotted looks like this: I am trying to fir a model to it using nlme.lme(). I am interfacing with R via RPy, and using the ...
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0answers
22 views

How to apply the random statement in my model?

i am trying to model the following data in SAS using proc glimmix and i would like feedback if i have modelled my data correctly. My data consist of individual chickens (ID) who are grouped by ...
0
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1answer
35 views

Repeated-measures, crossover analysis using linear mixed model in R

I have a data set that I am attempting to analyse in R and I am relatively new to the environment. My full data set contains 7 subjects (represented by Subject), that all receive 3 treatments ...
1
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1answer
37 views

The 'best' model selected with AICc have lower $R^2$ -square than the full/global model

I have used the R lme function (nlme package) to construct linear mixed models, with a single random effect (as a random intercept) and a varIdent variance structure on a fixed effect (that is a ...
6
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1answer
94 views

Relationship between paired t test and simple mixed model

The bounty I placed on this question expires in the next 24 hours. I have a psychological data set which, traditionally, would be analysed using a paired samples t test. The design of the ...
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0answers
25 views

Proc Mixed statement

Suppose I have a data set: ...
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0answers
45 views

Help with lmer in the lme4 package

I am new to using linear mixed models and would greatly appreciate any help I can get. I have an equation of the form $ y = X\beta + Zu + \epsilon$ where $u$ is a random effect whose covariance ...
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0answers
26 views

Understanding repeated covariance types in SPSS?

I am working in SPSS on a repeated measures linear mixed model and I am having a really hard time wrapping my head around how to select a "repeated covariance type". The options are: ...
0
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0answers
11 views

How to get/calculate confidence intervals for slopes of the continuous*categorical interactions?

Not sure if this should be in Stack Exchange or here, but here goes. I have a linear mixed model in SPSS, and I want the confidence intervals for slopes of the continuous*categorical interactions. ...
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0answers
26 views

How to perform a meta regression with a random effect model?Which model should I use?How to start? (beginner)

I have to perform a meta-regression, using mixed or random effects model, but I don't have any software (except Matlab) and I'm new on this topic (having a relativelly poor statistics background). ...
0
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0answers
30 views

Within-subject and between-subject fixed effects in mixed model

I've been trying to analyze some data using mixed models but I have some troubles to understand how should I include both within-subject and between-subject fixed effects in such models. Let's ...
0
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0answers
8 views

Negative Binomial Mixture in PyMC [migrated]

I am trying to fit a Negative binomial mixture with PyMC. It seems I do something wrong, because the predictive doesn't look at all similar to the input data. And the predictions for the parameters ...
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33 views
0
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23 views

MANOVA for mixed model with multiple repeated measurements

I struggle performing a MANOVA for a mixed model. I have the following columns: S - subject (1,...,N) B - in between group (B1, B2) W - repeated measurement - within (W1, W2) M - measured dependent ...
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0answers
19 views

How to model a multiplicative effect of a parameter

I am having difficulty in fitting a model on data. Basically, I have data about the evaluation of phenotypic property (i.e. hard) of 65 palm trees by 5 judges. As an evaluation scheme, each judge ...
4
votes
1answer
73 views

Longitudinal item response theory models in R

I'm trying to fit longitudinal item response theory (IRT) models in R. I have a test that was administered at multiple measurement occasions. I'd like to examine individuals' growth curves of factor ...
0
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0answers
12 views

Modeling paired data: Philosophical difference between using mixed effects model and using grouping-variable-level outcome

I am facing a problem of detecting change in infection rate after surgery in about 400 eye surgery patients. Crucial medical background includes the following-- About 30% patients have both eyes ...
1
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1answer
38 views

Interpreting the mathematical formula of a mixed effect model

I am a bit confused about the function of a parameter in setting up a linear mixed effect model (hierarchical/multilevel model). This is how I understand a (random intercept and slope) multilevel ...
0
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0answers
6 views

MLR equivalent for repeated measures, multiple correlated responses

I'd like to determine the best approach to determining effect sizes for a set of experimental data with multiple correlated responses. Due to repeated measurements and high correlation between ...
2
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2answers
76 views

mixed model: is it primarily used for prediction or explanation or both?

Inspired by this post on the difference between explaining and predicting. I want to ask is mixed model primarily used to get better explanation (such as, but not limited to, getting better ...
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0answers
41 views

Comparing slopes in mixed-effect model

My data looks like the attached picture. The dependent variable indirectly measured physical activity. I tried to use mixed-effect model rather than RM Anova, because my actual data is imbalanced. ...
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0answers
14 views

Site effect in GAM model

I am trying to build GAM model to see the effect of several environmental variables on the total abundance of one species. I have collected samples from three sites with three replicates from each ...
0
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0answers
25 views

repeated measures ANOVA - non-experimental data

For every year, for eight years, I have a set of projects (n=332). The number of projects that exist in each year varies (for example, some years there are 10 projects others there are 60). In each ...
0
votes
1answer
38 views

fitting LMEMs for repeated measures with no correlation between intercept and slope

For a simulation study, I contrast the power of different LMEMs for repeated measures. To get p-values, I use likelihood ratio tests where I compare a model including a fixed treatment effect with one ...
1
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0answers
21 views

Testing the random slope with correlated random effects

I have a mixed/random effects model $$\mathbf{y}_i=\mathbf{X}_i\boldsymbol\beta+\mathbf{Z}_i\mathbf b_i+\boldsymbol\epsilon_i,$$ where random effects $\mathbf b_i$ has variance-covariance matrix ...
0
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0answers
13 views

Choosing levels of random factor in a mixed model

My apologies in advance if this question is as much about experimental design as it is about statistics. I'd like to know if there is a "best" way to choose levels of a random factor in a mixed model. ...
0
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0answers
17 views

Split plot ANOVA or t-test

I did a study in which I wanted to see if a teaching intervention would have an effect on student learning. I nonrandomly divided students into two groups, a control and experimental group, and gave ...
1
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1answer
36 views

Hausman's test for all $\beta$s – comparing FE vs RE models

I fit several two level models in SAS using PROC MIXED: an empty model with multilevel structure (null), a model with a level 2 covariate (partial model), and a ...
1
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1answer
69 views

Random factor nested in two fixed factors

I have read Random effect nested under fixed effect model in R, but I have a doubt: My data is on germling survivorship, I have Temperature as a fixed factor (2 ...
0
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1answer
27 views

Fitted values of 'lme' function result

I fitted a linear mixed model with R as follows. ...
1
vote
1answer
42 views

SAS Proc Mixed model interpretation

I'm fitting a linear mixed model by SAS. There are 596 sectors and 8489 subjects. (each sector contains 10~15 subjects). Each subject is measured at most 6 times, so the total number of observation is ...
0
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0answers
24 views

MIXED modeling of 2 within-subject factors with 2 repeated factors and df

This is a novice question regarding MIXED models, denominator freedom degree, and long format (e.g., in SPSS). Most Mixed Model tutorials that I find address between factors and repeated measurments. ...
2
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1answer
58 views

Multilevel modeling: longitudinal data with within-subjects factors

I have a data set with experimental data that I am analysing with multilevel modeling. Data are structured as follows: 24 Sessions 6 Subjects per Session 10 Rounds per Subject There was one ...
2
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0answers
29 views

How would you model this random effects structure?

I have a sort of weird and complicated model design, and I'd like to get your opinion on how best to model the error structure. I have 100 sites, with each site falling into 1 of 4 different forest ...
0
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0answers
47 views

Alternative to MANOVA when group covariance matrices are heterogeneous?

I'm running into problems meeting some of the assumptions of MANOVA, namely homogeneous group covariance matrices and normality. I'm looking for an alternative approach where assumptions are not ...
0
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0answers
11 views

Parameter estimation of LMM with multiplicative measurement error in fixed co-variate - How?

I have a linear mixed model, with multiplicative measurement error on the fixed co-variate only (i.e. the random part is assumed to be measured without error). How could I best estimate the ...