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Parameters associated with the particular levels of a covariate are sometimes called the “effects” of the levels. If the levels that are observed represent a random sample from the set of all possible levels we call these effects "random."

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Implementation of REML estimation with observation weights

Given a diagonal weight matrix $W$, a standard implementation of weighted regression in OLS is to multiply both the design matrix $X$ and the response vector $Y$ by the square root of weights and then ...
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1answer
18 views

How to include nested data in a mixed-effects model using R?

I am analyzing data from bird foraging surveys using the lme4 package in R and I am interested in the effects of field size (area), among other variables, on swallow rate of use. The surveys took ...
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1answer
40 views

mixed effects model in repeated measurements

My question is conceptual. Suppose $n$ patients, where each one is measured at 4 different time points. The outcome is continuous. The patients are randomly assigned to two groups, intervention yes/no....
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1answer
24 views

Is it neccessary to test for serial correlation in a multi-level model

I am running a multi-level model looking at factors that explain attainment. There are pupil- and school-level predictors, and the school the pupil attends is modelled as a random effect. I have run ...
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1answer
19 views

Can delta method be applied for determining the between subject variability (random variance) of a function of X?

Say, for example, I square root transformed X such that it follows normal distribution, fitted a linear mixed effects model and obtained between subject variability (BSV) of sqrt(X). How do I now ...
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1answer
17 views

Equation for GLMM w crossed random effects and logit link function

I am working on a GLMM model with crossed random effects and I would like to write an equation from the output where the outcome is the probability rather than a log of the odds. ...
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1answer
28 views

Multilevel models - Which level should the random effects enter on?

I am currently studying the effect that a pollutant has on plant growth. The plants come from a few different regions, and it is assumed that plants from the same region share more in common than ...
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1answer
46 views

Is LMM (lme4) the right way to go? [closed]

I do realize that there are already some questions about the p-values in lme4 and the nested effects but I've got a somehow specific case and failed to find anything that applies to this. I have ...
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1answer
24 views

Random intercepts model with no constant, no fixed effects

My understanding is that the following model is a random intercepts model with no constant. Therefore, lmer provides a random coefficient for each group (since the constant is omitted). ...
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2answers
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How does a fitted linear mixed effects model predict longitudinal output for a new subject?

I fitted a linear mixed effects model using nlme package for aids dataset. Here, CD4 is the CD4 cell count, obstime is the time of observation, and patient is the patient id. My linear mixed ...
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1answer
33 views

How does one interpret the results of analysis with mixed model with baseline performance as random effects?

In a RCT investigating motor skill learning after stroke, patients were randomly allocated to 2 different groups ( i.e. with and without an intervention which was a robotic assistance during training)....
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37 views

Model fails to converge in glmer() after trying different optimizers

I am struggling with this specific mixed model which keeps failing to converge after trying different optimizers. In the model, the response variable is binary (0,1) with 4 numeric predictors and 3 ...
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1answer
20 views

Need help with fixed and random effect negative binomial models in R [closed]

This is my first time asking a question here. I am trying to develop a relationship between number of accidents on a road segment and some geometric and traffic variables. I have total 7 years of data ...
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21 views

the random-effects parameters and the residual variance (or scale parameter) are probably unidentifiable

I am working with 43 subjects who had token two differents beer and I would like to analysis the effect of both beer in HOMA variation. I have 4 different measurements of HOMA (before and after of ...
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1answer
127 views

Interpretation of Fixed Effects from Mixed Effect Logistic Regression

I am confused by statements at a UCLA webpage about mixed effects logistic regression. They show a table of fixed effects coefficients from fitting such a model and the first paragraph belows seems to ...
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1answer
35 views

What does it mean when a low number of quadrature points gives a very different GLMM fit?

I am interested in a logistic regression model with 10 fixed-effects parameters and random intercepts, which I can fit using the lme4::glmer function in R. The ...
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0answers
12 views

Mix Effects Survival modeling (coxme)

I have some experimental data looking at arsenic toxicity in mice and I'm trying to screen for potential biomarkers that associate with survival. I sampled mouse microbiome communities at 2 time ...
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1answer
55 views

How can I interpret the estimated random coefficients (e.g. random intercept) in a mixed model?

We know that random effects are estimated as a probability distribution rather than each individual random coefficients. Take the simplest random intercept model as an example: $biomass_{i,j}$ ~ $...
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cross-level interaction significant with three levels but insignificant with two levels

Help appreciated! I have run a multilevel model with two levels (students-classes) in which a cross level interaction appears insignificant (an interaction between a student-level predictor and a ...
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1answer
41 views

What is the difference between a Rasch model and a mixed-effects logistic regression?

I've recently been learning about the Rasch model. Previously I've used various kinds of generalized regression, including linear as well as logistic and "vanilla" fixed-effects models as well as ...
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1answer
28 views

Can I report fixed and random effects outcomes in one paper?

I am a health economist working with panel data for a paper I am working on, I use Hausman tests to determine if I should use fixed or random effects estimators in my analysis, for some outcomes ...
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0answers
53 views

What are the advantages of a random effects model versus a pooled OLS regression with cluster–robust standard errors?

Both models allow for explanatory variables that are time-invariant. I had thought that the advantage of a random effects model might be related to the fact that random effects models mitigate ...
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1answer
51 views

Scientific source for why reporting p-values of random effects is not meaningful?

I have read a lot about why most statistical packages do not report the significance test results of random effects (e.g. here) Is there any publication about this precise topic that I could use to ...
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55 views

Difference between random effect and fixed effect with regularization/prior

Let's say I have a random effect intercept. For example: lme4::lmer(yield ~ 1 + (1|Batch)) How is that different than just ordinary regression using ...
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21 views

Interpreting interacting random effects in lme4

My questions is about how to interpret the output from lme4 for interacting random effects. Our model is as follows: ...
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0answers
29 views

random intercept, random slope plus intercept, no random slope alone? [closed]

I measured running speed of 70 individual lizards. The lizards were siblings born of 7 mothers, 10 offspring each. The Lizards ran at 3 different temperatures, A, B, and C, where A < B < C, and ...
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63 views

Random effects in gamlss

I have a question regarding the gamlss package. I am attempting to fit a mixed effects model using the Befa Inflated distribution as follows ...
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0answers
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Longitudinal data Random effect of time 0 - meaning?

I have longitudinal data collected at three waves (in 2004, 2007 and 2011). The three waves have decreasing sample size, because is a follow up cohort study. I am interested in investigating the ...
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1answer
57 views

Understanding whether to use two-way effects [duplicate]

Using plmtest, I find that individual effects are significant (p: 7.327e-05); time effects are not significant (p: 0.1263); and two-way effects are significant (p: 0.0001197). Based on these results,...
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1answer
32 views

How does pooling work with crossed effects in multilevel models?

In Section 12.2 of Gelman and Hill, The authors mention that one of the main benefits of creating a multi-level model is that you can take advantage of "partial pooling". As an example, if you were ...
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0answers
34 views

Random repeated-measures linear mixed-effect model

I want to analyze how the number of ants of the species "A" is related to different environmental measurements (Temperature, relative humidity, and wind speed), number of flowers, number of ...
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1answer
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33 views

When is it OK to calculate the AUC for a mixed-effects logistic regression model without the random intercept?

I fit a mixed-effects logistic regression model in R with glmer. There is one dependent variable, one dichotomous predictor variable, and one random intercept. The ...
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0answers
11 views

Theory about LMM -design matrices for nested and crossed effects

I want to explore the details of the design matrices involved in Linear Mixed Models (LMM) with random effects associated with crossed and nested grouping factors. Of great interest to me, is also, ...
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36 views

Shared frailty model: frailty (random effect) correlated with independent variable WITHIN groups - a problem or not?

Dear CrossValidated community, Background: I would like to estimate a shared frailty model (see these lecture notes; the following draws on this document). It is a a random effects survival analysis ...
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lme4 How to interpret a random slope effec while there is no fixed effect?

I have a question regarding the interpretation of multi-level models. This is my first model: m1 = lmer(Y ~ x1 + x2 +(1| class), REML = FALSE, data=dataset) In ...
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1answer
55 views

Linear mixed-effects model equation for correlated and uncorrelated random slopes

I've been asked to provide a linear equation for a lme4:lmer() model that I report in one paper. I tried to adapt examples from http://rpsychologist.com/r-guide-...
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1answer
43 views

Can a random slope in a linear mixed model mask the effect of my intervention?

I want to assess the impact of my intervention in a repeated-measures design. I have subject as a random intercept in order to account for the dependence of measurements within subjects: ...
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0answers
32 views

Multi-level Models - Date as a Random Effect

Hi I was wondering if someone would be able to help me decide on the proper set up for a multi-level model using the lmer package. In my study, we are looking at heart rate in beats per minute ...
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Should geographic location always be included as a random model effect?

Under what sort of experimental conditions and/or objectives might someone be justified in modeling geographical location as a fixed effect (assuming that most times location is included as a random ...
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how are variance components for random effects calculated for mixed model when the effect is categorical?

I have a question about how variance components are calculated for categorical variables in mixed models. For example I have a cluster vector of (4, 4, 6, 6, 5). If the overall mean is 6, then the ...
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Have I adjusted for predictors I use as random effects?

I believe this is a rather straight forward question. I just read a research article in which it stated that: "[...] we used study centre as random effect, which also means that we adjusted for study ...
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Trying to understand a latent curve model in terms of mixed effects regression

I'm trying to understand exactly what the following model is trying to represent: (taken from Beaujean's Latent Variable Modeling Using R book) The text indicates that this is a random intercept/...
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1answer
188 views

OLS, Fixed effects or Random effects Model?

I am a little bit confused about type of model to apply because my type of data. I am interesting in get regression parameters for time (dependent variable) with independent variables= sex + age+ ...
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0answers
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Calculating proportion of variance explained by random effect in multinomial GLMM

I have a multinomial logistic GLMM with one random intercept. The number of response categories $C = 4$. Since a multinomial logit model consists of $C-1$ binomial logit models -- each pairing one non-...
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1answer
23 views

Random generation of wealth with normal distribution of two parameters? [duplicate]

I want to randomly generate the wealth of a group of people, with two parameters: age and height. Basically (not necessarily realistic): Rule 1. the older a person (allow decimals), the higher the ...
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0answers
54 views

running simple glmer (NULL) model returns warning message -R

I am running a simple model: ...
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0answers
14 views

¿Any suggestions? GLM, HLM, MLM Problem (lme4)

I'm new to Multilevel modeling and currently I been working on a business project and its data is related to multilevel modeling. I know a lot of things about how to approach this problem, but I will ...
2
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0answers
29 views

ANOVA for difference of means - is there a random effect due to population sampling?

I would like to know if a population sampling "random effect" applies in a very simple difference-of-means test. CASE 1: A toy scenario to setup the question: suppose we want to compare the ...