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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13 views

Big Misconception in the use of REML to estimate Variance Components?

I often hear from my classmates, and even in resources on the internet such as in the abstract to this paper, what I now believe to be a misconception regarding the motivation of using REML (...
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1answer
29 views

Random effects vs. Fixed effects in Twin Studies

I am conducting a study on identical twins, such that the data can be considered as paired observations. I want to run a co-twin control analysis on the data to study the relationship between the ...
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4 views

How can I use RLRsim to get for the results of a fitme() model (from the spaMM package)? [migrated]

I've found that the spaMM package fits my generalized linear models where others (e.g., lme4, glmmADMB) don't. Because my data is very uncooperative. I really need some kind of confidence intervals or ...
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1answer
15 views

permutation testing and mixed effects models

I am rather new to both permutation tests and mixed effects models, so forgive me if this is a ridiculous question. I would like to run a permutation test for a model that has a random effect, ...
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5 views

implication of intra-class correlation coefficient for panel data estimation

What does intra-class correlation coefficient imply for panel data estimation? If ICC is very high (0.9), is it ok to estimate the model using fixed effects (with clustered errors), or is there any ...
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7 views

Split random or fixed effects into categories

Consider a simple panel data model: $$y_{it} = \alpha_{i} + X_{it}\beta + e_{it} $$ where $\alpha_{i}$ could be either random or fixed effects. Say your data has a categorical variable $Z_{i}$ so ...
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25 views

Random effects for multiple social partners

I am a behavioral scientist attempting to estimate the degree to which animal subjects in my dataset exhibit consistent individual differences ('personality') in their social behavior. The dataset ...
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15 views

Algorithm for mixed-effects models with 100 random effects

I am wondering if there is any algorithm can estimate a mixed-effects model with 100 random effects, i.e., the covariance matrix $\boldsymbol D$ for random effects is 100$\times$100. I tried the ...
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9 views

Is it possible to do mediational analysis on trial-level data, including random subject and items factors?

I have words that are rated on several different dimensions. Each of say 30 subjects rates a set of say 30 words. I am curious if some feature of the words is related to some rated dimension of the ...
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27 views

How to read this table? Mixed effect models [closed]

Hello community! I have been lost trying to interpret this table! Could someone please help me out?
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1answer
31 views

Interpreting a mixed-effects meta-analysis using the metafor package in R

This relates to an earlier question. Mixed effects meta-analysis using metafor package in R It is very easy to perform a mixed-effects meta-analysis e.g. using ...
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19 views

Error structure: FE vs within-between RE

Model Setup My dataset is a country-year panel and I ran two estimations: A classical OLS model with country and year fixed effects $y_{it} = \beta x_{it} + \eta D_i + \mu D_t + u_{it}$ where $x_{...
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1answer
36 views

Random effects not appearing for some levels in lmer model - Why would that be?

Here's my code in R but I unfortunately can't share my data, and I can't reproduce it by randomly creating a data set. I can say that the data set has 1,561 cases....
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1answer
22 views

model specification: crossed random effect for item and subject with fixed effect nested (??) within items

In a previous thread I got the advice to run a crossed random effects linear mixed model with my data. Whilst working on the model specification, I came across a new question. In short, all ...
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1answer
37 views

Can unit/time dummies be included with PCSE or XTGLS?

I am currently working with a balanced time-series cross-section dataset (or a T dominant panel), consisting in 8 units (countries) and 32 observations (quarters) per unit. Thus, the dataset has 8 x ...
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1answer
22 views

multiple samples from each subject: nested random effect in lmer?

I have a simple design: one dependent variable (brain activity), a factor I manipulated with two levels (ct1 and ct2) and patients participated in both levels. So far so good. But for each patient, I ...
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100 views

Combining Fixed Effects and Random Effects Confidence Intervals, Is this Possible?

I estimated a random slope,random intercept model and have estimates of the fixed-effects $\beta_i$ and the random effects $b_i$. I also have their associated standard errors $SE_{\beta_i}$ and $SE_{...
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8 views

Is Random intercept by items “parasitic” on fixed effects tied to items?

I have the following model (simplifying to get to the point): Y1 ~ X1 + (1|subject) + (1|item) X1 is "confounded" with item, meaning each item takes on one and only one value of X1. I have been ...
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24 views

Are estimators of heterogenity variance and of the random-effects mean asymptotically independent?

In random-effects meta-analysis, there are many different methods for estimating the across-study heterogeneity, $\tau^{2}$ (including DerSimonian-Laird's moment estimator, ML and REML estimators, and ...
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28 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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16 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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19 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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57 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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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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1answer
69 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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24 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 ...
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41 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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14 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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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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60 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 ...
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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 ...
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1answer
40 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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24 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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35 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
32 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 ...
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1answer
95 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
43 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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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 (...
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0answers
51 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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22 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
65 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
57 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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20 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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0answers
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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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 ...
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2answers
229 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 ...
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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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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. ...