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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1answer
41 views

lme4: random effects

I have a simulated data set of 4 repeated measurements (measure) for 5 subjects (subj), 20 trials (trl) each. I am trying to fit a model with random slopes for age category with subject and trials ...
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0answers
17 views

Modelling time invariant variable as a random effect

I have a data set that consist of one-year claim information of individuals. Individuals can have zero claim, one claim and more than one claim in a year. Generally they have more than one claim and ...
1
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2answers
55 views

Random intercept turns insignificant - Interpretation

I am running a intercept model with intercepts varying across people in R. My independent variables are all numeric variables. My question is a general one: I saw already that it can happen that my ...
3
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0answers
45 views

Study on both hands of patients, mixed effects?

We want to test the correlation of a certain surgical procedure on the hand (carpal tunnel) and the development of trigger digit. We have both hands of the patients, some hands underwent surgery, ...
2
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1answer
36 views

Panel data estimation for country-fixed, time-varying share of y

I want to estimate the following equation using a panel data set with countries $i$ and years $t$, preferably in R: $$ y_{it} = \beta_1 \cdot x_{1,it} + \beta_2 ...
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0answers
25 views

Box cox for mixed models in R

Consider a mixed model generated using the lme function in R. How can I consider the Box-cox transformations of this model in R? I have seen similar questions being asked before but they did not give ...
0
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0answers
9 views

Panel model Estimation - 5 and 10 years Break [migrated]

I am trying to estimate the relationship between inequality and growth in a panel data of 22 countries for the period from 1985 to 2010, using fixed-effect and random effect. I want to use 5-year and ...
0
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1answer
18 views

Autocorrelation *across* random effects in nlme:lme?

I have response data measured at the site and month level. I wish to fit a year trend to the data and month to remove the seasonal trend. However, to avoid pseudoreplication, I have fitted year also ...
0
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0answers
22 views

Mixed effect partial proportional odds ordinal regression in R

I want to ask if there is a package in R that can fit and more importantly predict a clustered (random effect) ordinal regression with non-proportional ...
1
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1answer
39 views

How to specify a random slope only in glmer

I'm trying to build a glmer model and want a random effect of individual ID but only need the random slope. I've been searching the internet for awhile but I'm still not 100% sure how to specify the ...
1
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1answer
56 views

Hausman test for panel data

I am performing a Hausman test to decide whether to use fixed effects or random effects model. The results I get are as follows: ...
0
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0answers
26 views

Random effects model with time varying predictors and invariant outcome

I'm considering a random coefficient model with a time-invariant outcome and both time-varying and time invariant predictors. I have introductory knowledge on the topic. My outcome is a performance ...
2
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0answers
21 views

Heteroscedasticity test for random effects model in Stata

I have a panel data and according to Hausman, I have to use a random effects model. I know that in Stata I can use a modified Wald test, but only with a fixed effects model. I want to know a test for ...
1
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0answers
17 views

Fitting a multilevel AR1 in R

I have some short grouped time series data. I would like to fit a dynamic multilevel regression model in R, with random coefficients for the mean and first order auto-correlation in each group, and ...
0
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0answers
18 views

high standard error in random intercept model

I am fitting multilevel logistic regression to left without being seen (LWBS) by providers as dependent variable for each visit to 6 hospitals (random intercept of each hospitals). The total number ...
0
votes
1answer
34 views

Comparison between a multilevel and an unpooled model

Suppose we have fitted two models: a multilevel model and an unpooled model: m1=lmer(y~x+(1|group)) m2=lm(y~x+factor(group)-1) How can I understand which ...
1
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1answer
85 views

Fixed effects or Random effects model?

I am trying to understand the difference between fixed and random effects modelling. The panel data I have is in the form of basic longitudinal panel time series. I know that I can use the Hauseman ...
0
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1answer
21 views

Mixed-effects model without the random effect in the design?

Is it appropriate to create a mixed-effects model (for example, using SAS Proc Mixed) that specifies a random effect but does not include the random effect in the model itself? I ask because it seems ...
1
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0answers
55 views

Testing and correctly interpreting the significance of nested random effects

I'm building a series of relatively simple random effects models where we repeatedly measure a water quality variable, say conductivity (cond), in different watersheds (ws) and streams (st). Here, ...
1
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0answers
26 views

What is a case where including random correlation parameters decreases the error on the fixed effects?

I'm wondering about the effect of true correlations among random effects on the standard error of my fixed effects in lme4::lmer models in R. My assumption is ...
0
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1answer
67 views

Random effects for within subjects study in R

I have data which consists of subjective ratings. The ratings are done by different judges with each subject being judged under different experimental conditions. Each subject undergoes each ...
1
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0answers
22 views

Significant cross-level interaction despite lack of variance in level-1 slopes

I have a logistic HLM model with one level-1 predictor and without level-2 predictors. Random variance components are significant for intercepts, but far from significant (p>.5) for slopes. In my ...
0
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1answer
20 views

What is the difference between a random-effects regression and the negative binominal regression

My question is related to the topic if my data is overdispersed is random-effects poisson regression a suitable option? Thanks for any hint!
0
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1answer
19 views

Intercept in random effects mixed model no longer significant

When I add a categorical fixed effect to my mixed model (with one random effect and three continuous fixed effects) the intercept is no longer statistically significant. Does this mean that the newly ...
0
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0answers
8 views

How to interpret change in intercept when a random effect is added to a mixed model

I have a fixed effect model, constructed in SAS using Proc Mixed as: proc mixed data= etc...; model ca = p t s /solution; run; which yields the following ...
0
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0answers
13 views

Analysis of clustered data

I have records of $multiple$ visits from many different patients in several different clinics (i.e. visits nested within patients nested within clinic) and plan to perform an analysis that takes into ...
0
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1answer
28 views

Regression formula for negative binomial with random effects

I am doing a negative binomial regression with random effects. I have Panel data on 23 countries ($i$) across 28 years ($t$), with one dependent, one independent and three control variables. I do ...
0
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0answers
6 views

For forest research to see the interaction of environmental variables when to use GLMM

I am testing different environmental variables (altitude,slope,aspect,trampling,cut stumps) with tree density, seedlings and saplings, basal area and also with soil parameters like soil carbon and C:N ...
2
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1answer
94 views

R-Metafor: Meta-analysis and mixed effect model

This is an example of my dataset ...
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0answers
50 views

Comparison of crossed random effects (mixed models): lmer vs. MCMCglmm

I read that lmer can handle independent (often labeled as crossed) random effects in mixed models. It seems to be possible with MCMCglmm as long as groups for the random effects are uniquely labeled. ...
2
votes
1answer
49 views

Interpret effect of adding random effects to ordinal regression (R - ordinal package - clmm)

I know there are already lots of questions around this topic (especially this one and this one) but I haven't really seen anything that directly helps me (It will be obvious I'm not a great ...
0
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1answer
24 views

Mixed model (Multilevel) with two INDEPENDENT Random Effects [lmer]

I like to estimate a mixed model with two Random Effects, that are independent of each other and among themselves. I use Panel data with a nested structure (counties $j$ nested within regions $i$). ...
0
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0answers
20 views

How does NLMIXED estimate random effect for a 2-part (hurdle) model?

I am not a big SAS user, so this may be a naive question. I am using the NLMIXED procedure to estimate a random effects 2-part (hurdle) model, similar to as described here but with random effects for ...
1
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1answer
29 views

What software could fit an alternative specific random intercept multinomial logit model?

I have a dataset of around 30,000 people where each chooses one of 4 items: A, B, C or D. People are nested within the 600 areas. I want to fit a multinomial logit model, where random intercepts are ...
1
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1answer
74 views

lme4: Why is AIC no longer displayed when using REML [duplicate]

I have a simple question, understanding the basic usage of the lme4 package. I am following the tutorial by Bodo Winter ...
3
votes
1answer
77 views

Can we model non random factors as random in a multilevel/hierarchical design?

The distinction between strictly random variables (which ought to be modeled as such) and non random variables which some argue could be modeled as random if it is a hierarchical/multilevel model, is ...
0
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0answers
15 views

choosing the best structure of the random effects in a GLMM [duplicate]

I am trying to choose the best random effect structure in a GLMM, before starting with the fixed terms. To do that I include all the fixed effect and their interactions (beyond optimal model) and ...
0
votes
1answer
64 views

Predicting with random effects in mgcv gam

I am interested in modeling total fish catch using gam in mgcv to model simple random effects for individual vessels (that make repeated trips over time in the fishery). I have 98 subjects, so I ...
0
votes
0answers
10 views

P-values for random effects when using REML [duplicate]

I'm using JMP to fit a model for an unbalanced split-plot design. Because it's unbalanced, I'm using REML rather than EMS. However, I would like to get test statistics/p-values for some of the random ...
1
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0answers
29 views

lmer, effect of a ramdom factor in a covariate [closed]

hi I am doing a General Linear Mixed Model in R, lme4 package. I want to test the effect of a random effect on a covariate, as well as on the response variable. I thin that the command would be the ...
2
votes
1answer
40 views

Calculating heterogeneity (Cochrane Q and I^2 statistics) in random effect model

I want to ask whether I can calculate the Cochrane Q statistics and I^2 statistics in random effect model. I collected some data from different areas and want to compare the prevalence of allergic ...
2
votes
0answers
31 views

Fast Estimation of Random Effects with Measurement Error

Let $Y_{i}$~$Normal( Z_{i} , \sigma_{i}^{2})$ and $Z_{i}$~$Normal(0,\tau^{2})$, where $Y_{i}$ is a measurement, $\sigma_{i}$ is known measurement error, $Z_{i}$ is the unknown latent variable I want ...
2
votes
2answers
118 views

Can I include covariate as random effect in glmer?

I have a question regarding covariates in a GLMM. My model comprises a condition variable and a covariate. Crucially, my binomially distributed dependent variable can be interpreted only in dependency ...
2
votes
1answer
124 views

lmer and random effects

Here is somewhat simplified structure of the data I have, since fixed effects are quite straight forward, however, random effects are giving me a headache (like I said something new :) ): ...
0
votes
1answer
62 views

Is this logit model a multilevel model, and what is the correct way to model it?

I am analyzing a sample of about 6000 actions carried out by about 500 multinational companies in about 80 countries during a 6 year period. Actions are carried out randomly, and are not longitudinal ...
1
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0answers
25 views

Zero-intercept poisson regression model predicts better than a model with an intercept?

I have read some blogs/articles saying that intercept should not be suppressed. Recently, I used glmm.admb to model a ZIP (Zero-inflated Poisson) model which is giving better results without an ...
2
votes
1answer
101 views

Recommendation: Fast algorithm for logistic random effects?

What is the fastest algorithm for fitting a simple logistic 'random effects' type model, with only one level of categorical predictors? Another way of putting it might be a logistic regression with ...
2
votes
1answer
70 views

2 factor factorial model with random factors

Using lme4, how does one define a full 2-factor factorial model with both factors (and their interaction) being random? Specifically I am trying to recreate the ...
3
votes
1answer
62 views

Hausman test FE vs. RE in case that FE is not consistent

I have a twin panel data and want to estimate simple wage equation (interest in return to education). I use fixed effects(first differencing) to account for family background.(Based on: Ashenfelter ...
0
votes
0answers
51 views

Is my nested random-effect model non-hierarchical?

I have a problem with model structure because of the way factors are nested in a potentially non-hierarchical way. I'm not sure if I fully understand the issue but I can't find a way to specify the ...