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

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12 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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0answers
10 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
26 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
13 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: ...
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0answers
33 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
14 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
23 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
19 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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0answers
11 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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0answers
41 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
29 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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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 ...
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1answer
33 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
19 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 ...
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1answer
40 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 ...
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0answers
7 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
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2answers
85 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 ...
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0answers
16 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 ...
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0answers
23 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 ...
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1answer
335 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: $$ ...
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61 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 ...
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0answers
35 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, ...
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1answer
20 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 ...
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1answer
70 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) ...
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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 ...
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1answer
35 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 $\{x_1, x_2\}$. ...
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0answers
18 views

Proper Model Selection Randomized Block with Count Data

I have a data set on insect counts that looks like this: ...
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2answers
81 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 ...
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0answers
15 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 ...
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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 ...
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0answers
38 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
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0answers
26 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 ...
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1answer
38 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 ...
3
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1answer
50 views

Estimates of random effects in binomial model (lme4)

I'm simulating Bernoulli trials with a random $\text{logit}\, \theta \sim {\cal N}(\text{logit}\, \theta_0, 1^2)$ between groups and then I fit the corresponding model with the ...
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0answers
23 views

Optimal model/statistical test for my design?

I have a design with 1 between-subject factor and 2 within-subject factors as independent variables and 5 dependent variables (longitudinal accelartion, lateral acc., response time, first conscious ...
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0answers
10 views

Group mean centering predictors for crossed random effects

I'm fitting a mixed-effects model, in which I wish to test the effect of $X$ on $Y$, with crossed random intercepts and slopes for each subjects $S%$, and for each level of an additional grouping ...
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55 views

Model averaging predictions from lmer models

I am trying to model average predictions (not betas) and estimate confidence intervals from linear mixed models run with lme4::lmer. I have experimented with functions in the MuMIn and AICcmodavg ...
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0answers
62 views

How can the R-matrix in a mixed model be estimated?

In Henderson's Mixed Model equation: $y = X\beta + Zv + \epsilon$ where the joint variance of v and the error term is: $Var\begin{bmatrix} v \\ \epsilon \end{bmatrix} = \begin{bmatrix} G & ...
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0answers
84 views

How to report results from a linear mixed model “test of fixed effects” in SPSS?

What is the appropriate way to report results for linear mixed model based on the "test of fixed effects" table in SPSS? Is it just (F=xxx, p=xxx)? This isn't my data but this is an image I found of ...
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0answers
38 views

Comparing mixed-effects and fixed-effects models

Given three variables, y and x, which are positive continuous, and z, which is categorical, ...
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0answers
6 views

repeated measures mixed model with different number of measure per group

I have a an experiment with 3 groups. Two of these groups have the outcome of interest measured at baseline, 3 months and 12 months and one group has only been measured at baseline and 12 months. My ...
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0answers
40 views

Comparing different methods of discrete-time survival analysis

I'm investigating a discrete time survival problem (the units are months and exit times range from month 1 to 36). From looking around so far, it seems like there are a few different types of model ...
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0answers
17 views

Weighted Mixed model

I am trying to fit a standard mixed model to my data using lmer in R. I have both fixed and random effects. My fixed effect factor is say x, and my dependent variable is y I would like to make my ...
0
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1answer
34 views

What is the best approach for this set-up: RM ANOVA / MANOVA / Mixed-Models?

I have a simple dataset from a within-subject design. Each participant provided a verbal description of 3 stimuli. The descriptions were coded so that they consist from objects each belonging to 1 out ...
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0answers
9 views

Comparing trajectories of two outcome variables in longitudinal data

this is the situation: Study-type: prospective population-based (N = 4,000) with baseline (T1) and three follow-ups (T2 - T4) Between variable: cardiovascular health at T1 (good vs. poor) Within ...
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0answers
8 views

Model Selection In small clusters

I have a question please. Is ok to make model selection with MLE in small cluster in order to allow for comparison, and after getting the final model then fit the final model with REML? Since REML is ...
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0answers
13 views

How to include questionnaire data with behavioral counts in lmer() maximal logistic regression model?

I’m using a maximal logistic regression model to analyze some data. I would like to keep using this technique if possible, just include more data in the model. The main data I’m looking at is counts ...
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0answers
12 views

non-uniform residuals in repeated measures mixed model; larger residuals further in time

I am analysing data from a longitudinal study in SAS and see time-dependent patterns in the residuals. Subjects in four groups (A to D) were given a treatment at time=0; and continuous response ...
0
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0answers
13 views

Is GzLMM with linear linking function identical to (G)LMM?

Should I hesitate to report a "generalized linear mixed model with linear linking function (and assumption of a normally distributed target)" as simply a "(general) linear mixed model" in a ...
2
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2answers
84 views

Mixed Model Type-III Sums of Squares- R vs SPSS

The age old question of comparing sums of squares (SS) between programs has reared its ugly head again. I am trying to replicate output in SPSS, that was computed using Type 3 Sums of Squares, in R. ...