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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Random effects models / Integrate over the random effect

I am trying to do maximum likelihood estimation and trying to see if the problem can be formulated using a random effect model. Here is the problem description: There are $100$ pairs $(N_i, D_i)$ ...
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12 views

Fitting a Mixed Model with Random and Repeated effects in SAS

I have want to fit a linear regression with repeated measures and random effects. The data come from clinical observations. In CT images The dependent variable is the diameter of a lymph node lesion ...
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2answers
54 views

What is the right way to analyze a nested design in R?

I know that there are already a host of questions about nested designs but many of them haven't been answered or come from biological domains which I sometimes find hard to transfer to my domain. I ...
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1answer
69 views

Difference between random effect and random intercept model

I am looking at clustered data and because I was trained in economics I tend to look at fixed effects and random effects as solutions. An alternative would clearly be multi-level modelling. However, ...
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0answers
16 views

allowing for different variances between groups versus allowing for random slopes in lme

I have a data set that looks like this: Genotype Condition Trait A 1 0.0007 B 1 0.005 A 2 0.0003 B 2 ...
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1answer
42 views

Are best linear unbiased predictions (BLUPs) a good indicator of the mean value for that random effect member?

I have data on prices of houses in different districts, and would like to determine how expensive different districts are when it comes to buying a house. However, houses vary with respect to ...
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1answer
46 views

Is it possible to use the Breusch-Pagan Lagrange multiplier test (xttest0) in Stata for unbalanced data?

Is it possible to use xttest0 in Stata with unbalanced panel data? I want to test whether the I should use pooled OLS or random effects estimation. What does this test actually do?
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0answers
24 views

How to perform a meta regression with a random effect model?Which model should I use?How to start? (beginner)

I have to perform a meta-regression, using mixed or random effects model, but I don't have any software (except Matlab) and I'm new on this topic (having a relativelly poor statistics background). ...
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0answers
29 views

Within-subject and between-subject fixed effects in mixed model

I've been trying to analyze some data using mixed models but I have some troubles to understand how should I include both within-subject and between-subject fixed effects in such models. Let's ...
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22 views

How to estimate a dynamic Tobit model

I have data which correspond to a corner solution. The Tobit-model seems to be adequate for this data. However, I also wants to control for a baseline variable (t-1) and unobserved heterogenity. This ...
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0answers
27 views

Recovery of Standard Errors of Random Effects in Lmer

I'm analysing data with a nested structure with the lmer-function of the Lme4 package in R. I'm interested in the estimation of the confidence intervals of the random effects (is the score of class1 ...
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1answer
45 views

Testing significance of a random effect glmmADMB model

Below is the output from a model of novel object test scores fit with the nbinom1 (quasi-Poisson) option in glmmADMB. I used ...
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38 views

How can I include random effects into a randomForest

I'm not even sure that the question makes much sense, but I think I saw a couple of titles of papers where they proposed random forest with random effects. Is this possible in R?
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18 views

Do I need by-item effects in my lmer model, with gain scores as DV?

I'm attempting to fit a relatively straightforward linear model in R, but am in doubt as to whether by-item effects should be included in the model. Any input would be most appreciated! Study design: ...
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1answer
39 views

Residual specification for xtmixed

Suppose a random intercept model is to be fitted, like: $$y_{ij}=\beta_0 + \beta_1x_{1ij} + \beta_2x_{2ij} + \beta_3x_{3ij}+ u_{0j} + \epsilon_{ij}$$ where $x_{1ij}$ and $x_{2ij}$ are continuous ...
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22 views

Can time-invariant variables cause autocorrelation?

I am running a pooled OLS regression and Random effects regression. I have tested for autocorrelation for both methods. In the pooled OLS model I find serial correlation but for the RE model I find ...
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0answers
32 views

Intuitive explanation of “integrate out random effect”

We are trying to figure out an intuitive reasoning behind integrate out the unobserved random effect. The specific formula is: $f\big(y_i|x_i;\beta, ...
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0answers
21 views

Testing the random slope with correlated random effects

I have a mixed/random effects model $$\mathbf{y}_i=\mathbf{X}_i\boldsymbol\beta+\mathbf{Z}_i\mathbf b_i+\boldsymbol\epsilon_i,$$ where random effects $\mathbf b_i$ has variance-covariance matrix ...
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1answer
35 views

Hausman's test for all $\beta$s – comparing FE vs RE models

I fit several two level models in SAS using PROC MIXED: an empty model with multilevel structure (null), a model with a level 2 covariate (partial model), and a ...
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1answer
20 views

How does including a random effect, change the parameter estimate for a group level covariate?

I'll try and explain where I am getting stuck. I wish to model delay to treatment. I observe patients nested in hospitals. I have a mixture of patient and hospital level covariates. I suspect that ...
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13 views

What do I do if my sample for cross sections is not random in a panel regression model?

I am trying to implement a panel regression model, but there is one issue: both fixed effects estimation (FE) and random effects estimation (RE) require that the cross section sample be random. For my ...
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1answer
39 views

how to fit a michaelis-menten function with a random effect using the nlme package in R?

I am working on fitting a model using the nlme package in R. y is a saturating function of x, similar in form to a ...
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51 views

How to test for heteroskedasticity in Random Effects model?

I know how to test for heteroskedasticity using pooled OLS? But how can I do it after I have run a Random Effects model? If I find heteroskedasticity in pooled ols does it mean it is also present in ...
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0answers
42 views

How to detect outliers with longitudinal data?

I am running a pooled OLS and Random Effects (RE) model and I would like to test for whether there are any outliers. I know how to do this for OLS, but I just dont know how to do it for Random ...
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28 views

How would you model this random effects structure?

I have a sort of weird and complicated model design, and I'd like to get your opinion on how best to model the error structure. I have 100 sites, with each site falling into 1 of 4 different forest ...
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20 views

Should I control for random effects of participant in an individual differences design?

I'm trying to analyse a survey study in which I'm interested in the way that individual differences between my participants influence how they respond to my stimuli. The stimuli are pieces of writing ...
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16 views

Growth mixture models, “structural parameters”, and using a parameter with variance fixed at zero as mediator in regression model?

I am examining a paper that uses growth mixture modeling. They have estimated intercept, linear slope, and quadratic growth parameters. They have also estimated random effects for the intercept and ...
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53 views

Random effects and repeated measures: what would you choose as random effect?

I have a question regarding the use of random effects in order to account for a violation of the assumption independent samples. I have this discussion with my supervisor and we disagree about this ...
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1answer
53 views

When to use time dummies in multiple regression

When is it appropriate to use time dummies in multiple regression analysis? I am using pooled ols, random effects model, and fixed effects model. I have a period of 3 years. I don´t know whether it ...
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0answers
41 views

Estimated SD equal to 0 (lmer)

I'm trying to fit a mixed model of my data, but I'm getting the estimated between-subject standard deviation equal to zero. I need to estimate the between-subject standard deviation and within-subject ...
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0answers
80 views

R: glmulti for mixed models returns several best models, Automated Model Selection (multilevel analysis, hierarchical model, nested data)

I searched the entire web including this forum on some help on how to use the glmulti package in order to identify the "optimal" fixed part of a mixed model with a given random part. However, I could ...
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1answer
23 views

Effects in panel models “individual”, “time” or “twoways”

Panel estimators such the one implemented in the R package plm allow to estimate "individual", ...
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0answers
33 views

Fixed effect model is not significant without year dummies

My fixed effect model is insignificant when I don't include the year dummies $$\text{Prob $>$ F} = 0.7769$$ When I try other regressions the model is fine, for example Driscoll & Kraay ...
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39 views

question about multi-level modelling with nested data (R/Stata/SPSS)

I have a dataset composed of observations taken from 16 separate experimental panels, each nested into one of 4 conditions (Treatment A Level 1, Treatment A Level 2, Treatment B Level 1, Treatment B ...
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1answer
90 views

What makes the results differ for fixed-effects models vis-à-vis random effects models?

What makes the results differ for fixed-effects models vis-à-vis random effects models? The Cochrane Collaboration's website indicated that two models can produce different results for a meta ...
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0answers
40 views

Specific variance covariance structure in lmer

I have a dataset with cluster correlated data; multiple measurement on the same subject (not over time). I am trying to create two different mixed models using lmer in R with two specific variance ...
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0answers
19 views

How can dummy variables are able to add in Stata? [duplicate]

I use Stata to estimate Panel data with random effects. In my equation, I have 7 dummy variables which refer to 7 industries. Stata result omit my last dummy variables (industry7), but the rest of ...
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0answers
50 views

Is there any model that includes random effects with non-parametric data distribution?

I have a non-parametric (by which I mean non-normal) data distribution. I tried several transformations, but none were helpful. Now, I want to find a model where I can include random effects with the ...
2
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1answer
67 views

Interactions between random effects

I'm considering a mixed-effects model to try to understand factors that influence the number of ticks sampled on wild rodents. My data is nested so that I have one tick count per rodent, multiple ...
2
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0answers
70 views

Why do I get difference results when using pooled ols and random effects model?

I was wondering what the difference between pooled OLS and random effects model is? I know that random effects eliminates the time-constant effect. However, when i run my regression with pooled ols ...
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0answers
24 views

How to fit a random effect for only a subset of the observations (using R)

Say we have the following model: $$Y_i = \alpha + u_{j(i)} + \epsilon_i$$ for $i=1,\ldots,m$, for some groups $j=1,\ldots,J$, and $$Y_i = \alpha + \epsilon_i$$ for $i=m+1,\ldots,n$, where ...
2
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1answer
118 views

Understanding the Meta-analysis Model output in layman terms

I am conducting a meta-analysis from a large number of studies. In each study are compared weights of two groups (fishes with and without internal parasite). I am interested if the weight can explain ...
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0answers
45 views

Is there an R function to do a survival analysis with right censoring + nested + crossed factors

I have this dataset to model, but I'm not sure how to do it. I want to model the surviving probability of different populations of two species depending on a treatment applied. Populations should ...
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0answers
62 views

How to test for serial correlation with pooled OLS, FE an RE?

I have pooled data for 3 years, and I have come across the problem of serial correlation. Some books mention the problem of serial correlation when pooling the data. My question is: is it possible to ...
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0answers
65 views

Stata's xtlogit (fe, re) equivalent in R?

Stata allows for fixed effects and random effects specification of the logistic regression through the xtlogit fe and xtlogit re ...
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1answer
59 views

Correlated Random Effects Probit vs. GEE Population-Averaged Probit

My question relates to recent work on correlated random effects probit models (see these slides from Wooldridge) and comparing them to GEE population averaged probit models: Is one approach better as ...
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64 views

Fixed / Random Effects Model

I have the following kind of panel data set, without a time variable. 20 countries are the panel variable and provide data on 48 other countries. The independent variables are 6 (intercorrelated) ...
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43 views

Expected mean square of random effect in CRD model

Random effect in CRD model: \begin{align} y_{ij} &= \mu + \tau_{i} + \varepsilon_{ij} \\ \tau_{i} &\sim \mathcal N(0,\sigma_{\tau}^2) \\ \varepsilon_{ij} &\sim ...
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33 views

How do I partition variance among nested random effects for non-normal data and an unbalanced design?

I have a dataset of plant drought tolerance values (called TLP_DRY) that I would like to partition variance for among the nested levels Biome/Study site/Species to figure out whether most variation in ...
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24 views

Iterative solving of ML estimators

I have derived this likelihood function \begin{equation} \begin{split} &-\frac{1}{N}\log L(\eta,\beta,\mathit{\Omega})\\ &=\frac{1}{2}\log ...