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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6 views

Which is the dimension (or units) of the predicted random effects?

Consider a simple panel data (or multilevel model) with random effects. Say the dependent variable $y_{ij}$ is measured in output per year. The regression to be estimated is: $$y_{ij}= X_{ij}\beta + \...
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14 views

Why big difference in fixed effects estimate between fixed and random coefficient model?

I have panel data for all US counties over the past 4 years. I am interested in the relationship between two variables, Y and X, and have a hypothesis that X is a positive predictor of Y, but that the ...
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15 views

Why coefficients are different when pooled ols and random effect applied?

Does anybody know why the coefficients of an equation which is estimated by Random effect estimators and Pooled OLS is different from each other?
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26 views

Specifying and extracting random intercepts and slopes from GAMM using bam in mgcv

I have two questions about how to specify random effects structures in mgcv using bam. I'm using bam because I have a large data set (~15,000 data points) that consists of interviews with different ...
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0answers
22 views

Linear mixed models with two random intercepts?

I have observations for individuals that live in regions $R_1,...,R_r$, and that work in regions $\tilde{R}_1,\dots,\tilde{R}_r$, where for some individuals $R_j=\tilde{R}_j$. I also have a number of ...
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41 views

Mathematical derivation of correlation in dynamic panel data model

My question is about deriving a result in Cameron and Trivedi - Microeconometrics (2005) on page 763, section 22.5.1. The section's subject is Dynamic Panel Data Models - True State Dependence and ...
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23 views

FE and RE used simultaneousely

I am currently conducting a research aimed at finding an effect of corporate culture on stock returns (to measure the culture I performed text analysis to account for the frequency of specified bags ...
3
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36 views

Correlated random slopes and intercepts but non-significant random slopes. Can you have one without the other?

I am running a multilevel model. When I compare the random slope without a correlation (Model 2) model to the just random intercept model (Model 1) it is not significant (via likelihood-ratio test). ...
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13 views

Interpreatation of ratio of variances in random effects model - ICC-like quantity

I was reading this question and answer, and I was curious about a different ratio of variances than the ones described. Using this random effects model: $$ Y_{ijk} = \beta_0 + \eta_{i} + \theta_{j} +...
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0answers
15 views

Nested GLMMs: which are my random factors?

I am analyzing the number of seed capsules between different genotypes (A,B and C) I have 4 replicates for each genotype and in each of these replicates, I have 8 plants. Here is an example of the ...
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56 views

Hausman Test interpretation is based on the p-value? - R output

I obtained the following output after running the Hausman test: 1) CASE 1 Hausman Test chisq = 13.943, df = 4, p-value = 0.007478 alternative hypothesis: one model is inconsistent 2) CASE 2 Hausman ...
2
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1answer
23 views

Should I be using season as a random or fixed effect?

I am a marine turtle researcher attempting to understand the effect of a harmful algal bloom on our turtle capture rates and the body condition (BC=mass/length^3) of captured turtles. Field ...
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18 views

Two nested random factors, planing an experiment

I'm planning an experiment (described below), and I want to be sure that the experimental design is correct, and I'll have no trouble later on when analyzing the data. I want to know if the ...
2
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1answer
37 views

What to conclude about these models? Random intercept + Fixed Slope vs. Random intercept and Slope

In the 'nlme' R package, for instance, I ran the following models: ...
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23 views

include random effect in model

I am having problem deciding wheter to define a variable as a random effect to include in our logistic regression model. Any help on this subject would be most appreciated. In this model, we are ...
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3 views

Failing to implement random individual-specific variables in mlogit and gmnl models [migrated]

I have a response variable that is 4 categories of behaviors (ly, rs,al and fd). I am trying to use a multinomial model with 7 habitat-related predictors as fixed factors and individuals ("bird.ID") ...
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27 views

Cohen's d in pre-post meta analysis based on means and SD

As follow up on this question:I want to incooporate studies using different continues outcome in a meta analysis using SMD. I am following this guide and I do not fully understand how to calculate the ...
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1answer
26 views

Time as random effect or fixed effect in glmmADMB

I have a longitudinal dataset where patients have a measurement with a date, currently coded as time from end of treatment (days). Now, I want to build a model. Roughly, a zero inflated Poisson model ...
2
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1answer
94 views

Mixed model random effects term is arbitrarily correlated to dependent variable, does it bias model?

I have a logistic mixed model where a random effects term I am thinking about including is totally arbitrarily related (in a non-informative way) to the response variable. I would not include it as a ...
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1answer
38 views

Is least square dummy variable model better than random effects model?

I have a panel dataset with one dependent and twelve independent variables. There are 50 individuals with data for 100 days. Theoretically, most of them should be significant. First, I checked for ...
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0answers
7 views

Long-tailed random effect posterior distribution from unbalanced design

I am using MCMCGLMM to estimate the effect of some factors on a trait. The model is constructed with $Y \backsim B*S$ to find an interaction effect of factor B (...
2
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0answers
48 views

Can a random effects intercept variable be highly but coincidentally correlated to a response variable?

Issue- I'm creating a logistic mixed model where the response variable (if a plot falls within an active bird lek area) is highly related to a term I may include as a random effects term (grazing ...
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20 views

Multilevel modelling in JAGS: Unable to resolve node

I am building a multilevel model, where the time is on the first level and countries are on the second level, in JAGS (JAGS version 3.4.0). I want to build varying-slope-varying-intercept model, like ...
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1answer
63 views

Principal component analysis with random effects?

How can I do a Principal Component Analyisis considering also the Random Effects? (*) Is there any R package able to do so? Something like PCA+lme4 or PCA+nlme. (*) I mean I want to transform my ...
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1answer
42 views

Testing for random effects: Breusch-Pagan Lagrange multiplier (LM)

So I have a panel data with two time periods. My dependent variable is an index that lies in the range of 0 to 1. I did a Breusch- Pagan test (in stata) to see whether I should use random effect or ...
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19 views

Why does glmer break when I remove a subject?

I'm working with the epilepsy data set from Applied Longitudinal Analysis by Fitzmaurice et al. (http://www.hsph.harvard.edu/fitzmaur/ala/epilepsy.txt). In this trial, 59 patients are split into a ...
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24 views

Expectation of y given u when it follows Poisson distribution

So I was reading Generalized Linear Models with Random Effects by Youngjo Lee, in chapter 6 about Hierarchical GLMs there's this example: Suppose $y|u$ is Poisson with mean $\mu = E(y|u) = exp(X\beta)...
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0answers
18 views

Hausman Test- FE v. RE

I am estimating the parameters of my coefficients with logistic regression and I have unobserved heterogeneity. It is also a rare event. One of my primary independent variables is significant ...
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0answers
12 views

Linear Mixed Model with few and ranked subjects

I am studying linear mixed model recently, and my data have only 6 subjects and those are ranked groups of observations (Tier 1 customers > Tier 2 customers > Tier 3 > ... > Tier 6) The formula looks ...
1
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2answers
129 views

Industry and Year Fixed Effects

I hope someone can help me as I am stuck with this problem for quite some time. I have panel of S&P500 companies from 2010 - 2014 and I want to run a regression including industry and year fixed ...
2
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1answer
26 views

Using a Fixed-Effects ANOVA to help decide whether to conduct a multilevel analysis

Heck et al (2013) write that Generally, the first step in a multilevel analysis is partitioning the variance (referred to as $\sigma^2$) in an outcome variable into its within- and between-...
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0answers
8 views

predict new level using lme4

i want to predict air temperature by surface temperature using lme4. my code is: plsttest=predict(mod.xm,lsttest2,allow.new.levels = T). My sample data has 19 stations and each station has 45 days. ...
0
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1answer
36 views

Interpreting results of a Linear Mixed effect Model

I am trying to implement a Linear Mixed-Effects Model in Matlab. I have many repeated measures of some features in a longitudinal data set of 51 people. I considered a random intercept that varies by ...
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19 views

Nested effect in GLM

I am sorry that my question repeats many others already available here. However I have read many of them (e.g. this, this and this) as well as other documents and I am still not sure about my model. ...
0
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1answer
73 views

sjPlot: probabilities. How to interpret?

I am running the following model in R: model = lmer(Tau ~ ageS*days+YrsOfEds*days+sex*days+tract*days + (1|SubjectID), data=long) With this model I am ...
0
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0answers
21 views

Nested mixed experimental design with crossed factors for laboratory validation procedure: how to model it?

I have been asked to analyze the following laboratory experiment: 14 donors’ red blood cell samples are typed for rare antigen-asset recognition by an automated procedure (machine), which returns a ...
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0answers
8 views

glmer returning more random effects than specified?

I am estimating a model of the type (logistic regression with random slopes and random intercepts clustered by the variable ID): ...
0
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0answers
8 views

Using additional data to improve random effect estimates in multilevel model

I've got a set of measurements (axonal transport measurements for individual axons nested within animals in two treatment conditions: drug vs control) which I currently analyse using a random ...
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0answers
29 views

Queries regarding 'logistftest' function of logistf package for model comparison

I am a user of r package ‘logistf’, I have 2 queries regarding the ‘logistftest’ function when doing model comparisons, I would appreciate if anyone can give helps. I am comparing two models (one is,...
0
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1answer
33 views

'random intercept only', 'random slope only' and 'random intercept and slope' models

I have a terminological question about the use of the terms random intercept models, random slope models and random intercept and slope models. Through my readings, I find that most authors use the ...
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0answers
42 views

Fixed Effect, Random Effect vs. Mixed effect and distribution assumption

From my econometrics class, we have learned that the difference between fixed effect and random effect is the assumption on the unobserved heterogeneity of the group. If one were to use random effect, ...
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0answers
9 views

Linear mixed effects models: random intercept has a VPC of 0.56% yet significantly increases model fit?

So basically what I said in the title. The model is based on data from an experiment where participants look at faces and makes judgement on them. I have a sample of 40 faces and 3500 participants. ...
8
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0answers
94 views

Specifying prior for effect size in meta-analysis

My question concerns priors on effect sizes, in my project the measure is Cohen's D. Through reading the literature, it seems vague priors are often used, such as in the well-know eight schools ...
0
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0answers
6 views

GLMER casemix without random slopes

Imagine we're evaluating a large group of cars (our random effect) for reliability, by looking at data on various driving conditions (our fixed effects). We come up with a GLMER model that ...
0
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0answers
34 views

Changepoint mixed model R2jags

Can anyone suggest a way to code a changepoint model in JAGS (I'm using JAGS within R using R2jags) for the variance parameter of a random intercept effect? I am using the data set sleepstudy from ...
0
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0answers
38 views

Assistance with methodological procedures for (panel data) [investment/GDP]

I am attempting to see the relationship between FDI and Economic growth. So my two variables are FDI and GDP growth (I am also not opposed to using GDP per capita). My data is panel, as I am using 59 ...
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1answer
24 views

Hausman test for models with different regressors

I want to know if I can run a Hausman test for Random Effects and First-Difference models with different regressors? For Example: MODre = X + Y + Z MODfd = X + Y + C Where X, Y, Z, C are some ...
3
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0answers
50 views

Controlling for individual in nlme when most individuals only measured once

I am trying to model growth using nlme for a number of individuals over four time periods. My question is, did growth differ over time? Some individuals were measured twice or more, perhaps as a young ...
2
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0answers
68 views

Interpreting the variance of random effects in Mixed Linear Models

When fitting the following simple model, using the 'lme4' R package and including a fixed and random slope term, I get: ...
2
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1answer
22 views

Random effects model: Observations from the same level have covariance $\sigma^2$?

I'm trying to understand what the following means (or how it's displayed): For a one way random effects model: $$Y_{ij}=\mu+\alpha_i+\epsilon_{ij}$$ $\alpha_i \sim N(0,\sigma_A^2)$, $\epsilon_{ij} \...