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

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15 views

Mixed-modeling when no observation contributes both X and Y

I'm working on a project investigating the relationship between (let's say) a face's perceived masculinity and its perceived competence. There was a large number of face stimuli (80). Two completely ...
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1answer
17 views

Interpretation of model comparison with random slopes using lmer in R

I have a large data set with repeated measurements of same blood value (co) (2 to 7 measurements per patient). Each measurement is coupled with time which is the time interval between surgical ...
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3 views

change co-variance structure for linear quantile mixed model for animal breeding

I'd like to analysis my data (animal breeding) with linear quantile mixed model. Lqmm package in R does that but co-variance structure do not know A (relationship numerator matrix is Sparse matrix) ...
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14 views

mixed model with non-normally distributed data

I have a database in which a group of patients was assigned to one of two treatment arms. I have to find out if there is a difference in the evolution of a particular biomarker between these two ...
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0answers
21 views

Random slope and random intercept correlation at every level of X

Lets say individuals are nested within each ID and I am trying to a predict level 1 outcome Y from a level 1 predictor X1 or X2 with random slopes and intercepts. X1 and X2 are equivalent to each ...
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1answer
23 views

split-split plot design with unbalanced repeated measures in lme4 or nlme (SAS translation)

I am sorry if this answer has been answered before but most answers here (e.g. here, or here ) do not really adress my issue (or maybe I just do not see correctly how they do. I want to use a (linear) ...
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0answers
10 views

Parallel SAS computing in HPC cluster [migrated]

I am working in the simulation of a nested meta-analysis model through a HPC cluster. For doing this, I use SAS under UNIX environment and I am trying to run in parallel the following code that I ...
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2answers
47 views

Mixed model for learning data

I’m working with data from a learning experiment in birds and I have some doubts I hope you can help me clarify. I'm interested in comparing the performance in a learning task between male and female ...
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1answer
12 views

Can one use an observation level random effect in a binomial model to account for overdispersion?

I had some proportion data, namely the proportion of seeds retrieved from birds. I fed different types of seeds (100 each) to a bird species and tested how different characteristics of the seeds ...
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2answers
84 views

Random slope and intercept correlation. Not consistent in output vs manual calculation

Lets say individuals are nested within each ID and I am trying to a predict level 1 outcome Y from a level 1 predictor X with random slopes and intercepts. Using the nlme package in R, I ran the ...
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37 views

Are interactions between continuous predictors a problem in mixed models?

I am interested in the effect of within-subjects treatment Z (two levels) on my dependent variable Y (which is measured under various conditions). I measured Y at the start of the experiment as a ...
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15 views

syntax rules for specifying multiple random effects in lme4 [duplicate]

I’m trying to get my head around the lme4 syntax for multiple random effects. I know there is lots of information out there on the topic, but I still haven’t found a source that provides clear ...
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55 views

Post hoc comparisions in many groups

I met such problem. I have measured the respiration of animals in in 5 time intervals. Within each interval I have animals asigned to 4 treatments. In my main analysis I consider both: treatment and ...
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1answer
56 views

Nested mixed effects with lme4

I am trying to analyze data from an experiment using lme4. In the experiment, subjects saw either dark or bright versions of 50 stimuli (between-subjects; fixed effect "brightness"). All subjects saw ...
3
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0answers
40 views

Logistic Regression Model with Non-Independent Regressors

I'm looking to create a model that takes into account multiple logistic variables in an ordered process. To illustrate, what I'm trying to do is similar to the following: ...
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0answers
16 views

Strange predict() results from GLMMadmb after adding Zero Inflation

I am attempting to model abundance of a species based location groups and environmental parameters. I've encountered a problem with the predicted values from these models that is associated with ...
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0answers
3 views

How can I test the slope difference in generalized mixed model with ordinal response

I have fitted a generalized mixed model with ordinal response in SAS. The link function is a cumulative logit. There are three covariates are ...
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1answer
73 views

Using individuals as a random effect

I would like to compare the average gene expression of three different genes in three different brain structures under two different conditions (see the table below). All means have been ...
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2answers
48 views

What's an example of a situation in which it makes sense to assume random slopes but a fixed intercept?

I'm referring to multilevel modelling. Field (2013) writes: It’s worth noting that it would be unusual in reality to assume random slopes without also assuming random intercepts, because ...
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1answer
31 views

BIC in Item Response Theory Models: Using log(N) vs log(N*I) as a weight

In IRT software packages and in the literature it is common to calculate the BIC as $$ \mathrm{BIC} = -2 \cdot \mathrm{logLik} + \log(N)\mathrm{Npars} $$ where $N$ is the number of rows in wide ...
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0answers
21 views

questions about ancova model with both random and fixed effects

I have the following data (I show part of the data below) and would like to consider the ANCOVA model with type (a factor with levels 1 and 2) a fixed effect and batch a random effect nested within ...
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0answers
11 views

How can I control for age when running a mixed model?

If I put age as a factor, I will not be controlling this variable, right? I wonder how I can control that since I have noticed that age influences my dependent variable, but I am not interested in ...
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0answers
12 views

Mixed effects model instead of repeated measures anova

Considering similarity of Two Way Mixed Factorial Designs on http://ww2.coastal.edu/kingw/statistics/R-tutorials/repeated.html and Mixed Model approach on ...
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38 views

linear mixed effect model

I have a question related to application of linear mixed effect model. I have land use data in percentage which is the predictor and water quality score(ex. 100) as response variable for 100 areas. ...
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36 views

Split Plot Design? lmer analysis

I need advice regarding the analysis of a project that I am working at the moment. Here the picture of the experiment: We have an RCBD with four blocks. Within each block there are 5 plots. Each plot ...
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0answers
18 views

Two separate or a single mixed-effects model?

Lets say my data is exam results of students nested in schools and there are two kinds of schools: private and public ones. Now, what I am interested is the variance between private and public ...
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5 views

I need to create a macro in SAS to repeat PROC MIXED in a large data set [migrated]

I am currently working with a data set of 760 metabolites. These metabolites were provided to 15 bacterial species. Further, their growth was monitored at 2 optical densities (OD), in triplicate. ...
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62 views

Longitudinal data analysis where meaning and metric of response variable varies over time

Determining what factors predict change over time is a topic of investigation in many fields and there are a variety of readily implemented methods for analysing repeated measures in the same metric. ...
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15 views

Explaining mixed-model interactions with ANOVA?

I have searched through the answers on this forum and I couldn't find any detailed explanation to my question about linear mixed models. Here is my setup: 4 groups with treatment X (one of which is ...
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0answers
17 views

lmer: How to determine the weights?

I want to do a meta-analysis with lme4, where for each study several values $(x_1,y_1),(x_2,y_2),...$ are reported. These values have a linear relationship, so I want to use a mixed model with study ...
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1answer
24 views

Crossed & nested random effects in lmer

I'm trying to get the specification correct for a crossed and nested effect model. Suppose I want to cross Sample & ...
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0answers
13 views

Intra-individual covariance matrix in lme4

I wonder, why do not need to specify the structure of the variance covariance matrix and the lmer function library lme4, since using the lm function library nlme this is possible. Thank you.
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0answers
26 views

Normalize data with kurtosis > 1 for one group

I want to model my variable using mixed linear modeling, but the problem is that target variable has a very high kurtosis for one group. The distribution is totally normal for other group. ...
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25 views

Specification of mixed model structure in glmmLasso

I am having difficulties specifying the appropriate structure for nested/random effects in a mixed model that I am trying to pass through the 'Lasso' shrinkage algorithm. I am using the package ...
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1answer
17 views

Duplicate AICc values for multiple models with interactions

I am going through a model selection process with a mixed-model with 3 variables: A, B, and C. B and C are orthogonal factors. B or C may interact with A, so my full model would be: fixed: ...
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1answer
63 views

Mixed models: wrong random intercepts and interpretation issues

I have a dataset of individuals that participated in several races, but not all individuals did every race. Of every individual I have their average speed. My goal is to have a measure of how ...
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41 views

Anova (missing F statistics), Ancova and mixed modelling on nested dataset

I am performing an analysis in R and wonder how to do it since different methods return very different results. My dataset contains Samples and SubSamples as nested random effects and Type, Dose and ...
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12 views

Variance matrix for model errors

I am having trouble with understanding how can I write out the variance matrix for model residuals. I have a very simple data with 6 observations: ...
2
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2answers
49 views

getting degrees of freedom from lmer

I've fit an lmer model with the following (albeit made up output): ...
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0answers
18 views

How does glmmlass work for Linear Mixed effect model?

When I used the glmmlasso for a linear mixed model (gaussian), I got a warning message: ...
2
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0answers
41 views

Compare sample means of normal distribution with autocorrelation issues

Please forgive me if this is a naive question, but I haven't been able to find an answer in my stats books or online. I'm working on a fish tracking dataset that consists of detections of tagged fish ...
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0answers
26 views

Least Squares Dummy Variables vs. Mixed Effects Regression

I am aware this terminology is more generally used in the context of panel analysis, but I have datasets of individuals clustered within households, which I believe (according to my understanding) can ...
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1answer
28 views

Mixed way ANOVA

I have two variables (group, achievement level). I want to check the effect of an intervention on different achievement levels. For example, I want to check whether there is an increase in achievement ...
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0answers
34 views

Linear mixed model with two correlated dependent variables

I'm using the swissmunicipalities dataset in the package sampling of R. I consider two correlated dependent variables, the population between 40 and 65 (Pop4065), and the population aged 65 or more ...
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14 views

Design of experiment - coding, method to analyze data

We have data from an experiment where there are two groups. They are both measured at time 0, before training and one of the group is trained the other is not. We measure some outcome variables ...
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44 views

Piecewise HLM with nlme [closed]

I have two time periods of interest and four observation points(0 months, 4 months, 12 months, 16 months) for my subjects. The first time period of interest is between observation 1 and observation 3. ...
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3answers
37 views

When does the EM for Gaussian mixture model has one of the Gaussian diminish to exactly one point and have zero variance?

I had implemented the EM algorithm for mixture models as follows: For the E-step I compute the soft-counts of assigning each point $x^{(t)} \in Data_n$ to an individual cluster $j \in \{1, ..., K \}$ ...
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0answers
13 views

Correlated subjects in linear mixed model

I have a continuous variable that I want to model using linear mixed model. Goal is to measure two effects related to city and data source from which the variable came. The target variable is in fact ...
1
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1answer
36 views

can I apply loess or spline regression in mixed model?

My situation right now is that I have the mixed model with quadratic term but it doesn't perform very well. So I am wondering if I can apply loess or spline regression to the mixed model instead of ...
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0answers
25 views

Interpreting factor when intercept is not significant

I'm in the middle of doing a mixed model analysis. I'm interested in assessing the effect of a continuous covariate and a categorical factor (with two levels), including their interaction, on a ...