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

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4
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1answer
26 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 ...
0
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0answers
9 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 ...
0
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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 ...
0
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0answers
7 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 ...
0
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0answers
35 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. ...
1
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0answers
33 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 ...
1
vote
0answers
11 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 ...
0
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0answers
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. ...
1
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0answers
32 views
+50

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. ...
0
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0answers
12 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 ...
0
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0answers
7 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 ...
1
vote
1answer
18 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 & ...
0
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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.
0
votes
0answers
25 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. ...
0
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0answers
23 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 ...
1
vote
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: ...
1
vote
1answer
52 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 ...
0
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0answers
37 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 ...
1
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0answers
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
votes
2answers
42 views

getting degrees of freedom from lmer

I've fit an lmer model with the following (albeit made up output): ...
1
vote
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
votes
0answers
40 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 ...
0
votes
0answers
19 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 ...
0
votes
1answer
27 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 ...
0
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0answers
27 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 ...
0
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0answers
12 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 ...
1
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0answers
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. ...
1
vote
3answers
34 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 $j \in \{1, ..., K \}$ ...
0
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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
vote
1answer
34 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 ...
0
votes
0answers
24 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 ...
0
votes
1answer
48 views

How to translate percentage decline into a regression slope?

I want to model a negative relationship of count/binary data over 10 years with a known value for the decline rate (in percentage). However, I have problems in calculating the correct slope value for ...
0
votes
0answers
8 views

repeated measurements with different subjects over time

I am measuring methane oxidation over time. I sampled at 5 different time points (T1, T2, T3, T4, T5) to see if oxidation had occurred, each sampling time, say T1: I sampled 5 bottles, and I sampled ...
2
votes
2answers
94 views

GLMM validation: weird qq & fit vs residual plots

I'm encountering problems with the results of a glmer model (lme4-package). Im trying to answer the question, whether a beaver ...
1
vote
0answers
23 views

Impute missing data for mixed effects models?

Although I will not provide a reference, because I cannot recall where I did read it, I have several times read or heard that missing data is accommodated automatically in mixed models. Can anyone ...
0
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0answers
24 views

Are the statistical words contrasts and post hoc synonymous?

I have implemented a linear mixed-effects model using lmer{} model in R and used glht to to ...
12
votes
1answer
348 views

Why do mixed effects models resolve dependency?

Say we're interested in how student exam grades are affected by the number of hours that those students study. To explore this relationship, we could run the following linear regression: $$ ...
2
votes
0answers
72 views

Polynomial contrast in mixed anova with type III SS

I'm trying to replicate SPSS output in R for a mixed ANOVA with a polynomial contrast to test a linear trend. I fitted a mixed ANOVA in R (see code below), but I can't figure out how to get the ...
1
vote
0answers
45 views

Use lmer to test main effects and interaction

I have to solve a problem using a linear mixed model (lmer). Six subjects performed two tests, (test1, ...
0
votes
1answer
21 views

Specification of mixed model effects

I have a study design with a between subjects factor (treatment: verum vs placebo) and a within subjects factor (time: before vs after). Subjects were entered into the model as a random effect. So ...
1
vote
1answer
88 views

Likelihood ratio tests using ML vs. REML

I am using Mixed effects models (nlme package in R) to choose the model with the best random and fixed effects. I am following the procedure of Zurr et al. (2009) ...
0
votes
0answers
17 views

How to test for interactions of continuous measure with two repeated-measures factors in R?

I am doing an items analysis of difficulty ratings of a large set of math problems which were constructed to represent the factorial combinations of two binary factors, feature1 and feature2. The ...
1
vote
1answer
40 views

SAS NLMIXED proc and LOGISTIC proc results different

Consider a dataset $Z$ with $S\in \{0,1\}$ as binary response variable and 2 predictors $\{x_1, x_2\}$. ...
0
votes
0answers
20 views

Proper Model Selection Randomized Block with Count Data

I have a data set on insect counts that looks like this: ...
0
votes
2answers
99 views

Model Assumptions: LMER / GLMER Model where Dependent Variable is a Percentage

I am attempting to build a model for the following dataset: Level 1 Observations (Product-Level): 89000 Level 2 Observations ("BU_SBU" Department-Level): 135 Unfortunately I cannot share a sample of ...
0
votes
0answers
16 views

Boostrap confidence interval mixed model

I have have about 1000 data points (x,y,z). I am fitting a mixed model to the data, using lmer in R model = lmer(z ~ x + I(x^2) + (1|y)) I am interested in ...
0
votes
0answers
24 views

Comparing Binomial Success Parameters in a Stratified Approach - An Example in Biostatistics

I would like to contrast the effectiveness of drug treatment and surgical treatment in a study with the following data. Each row represents one trial, and each trial uses either drugs or surgeries to ...
0
votes
0answers
41 views

Marginal and Conditional $R^2$ for GLMM

I am trying to calculate $R^2$ (variance explained) for a set of data using GLMM's, and . Here's some dummy data. ...
2
votes
0answers
27 views

Reverse-engineering a (custom goods) pricing algorithm - each db row has: | 3 factors | 2 co-variates | price | (I have over 100k rows of data) [closed]

just wanted to mention up front that my question doesn't concern dynamic pricing, price optimization, revenue management, etc. No time series analysis either. It's just a simple multivariable ...
0
votes
1answer
42 views

Controlling nuisance covariate in lmer

I want to control for a nuisance covariate in a linear model. Since the covariate interacts significantly with one of the fixed factors, the homogeneity of regression slopes assumption is violated for ...