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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11 views

Error message in a nested Mixed Model in lme4

I'm trying to model the effect of a biomarker, Pentraxin3 on another biomarker, IL6 in a mixed model to account for correlations between the repeated measures and for correlations between the ...
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6 views

Choose between models FE vs RE vs Pooled OLS

I have quarterly data for 3 countries for a period of 10 years. Number of observations = 123. I have the following two questions: I would like to know what tests should I perform to choose between ...
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13 views

Analyzing frequency of medical procedures by hospital and patient characteristics

I'm working with state-level HCUP data. This mostly includes patient characteristics (age, gender, race, etc.), diagnoses and procedures, as well as info on the hospital including bed size, ...
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0answers
7 views

Random effects structure for within-subject / repeated measures design in glmer

This post is somewhat related to this one, however with another focus. I have repeated measures data of plant species richness with the following variables: ...
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1answer
31 views

Reporting of Heterogeneity in Metaanalysis

The background is a forest plot of a meta-analysis which is reported to have been calculated with a "random effects model". The pooled effect is reported as a standardized mean difference (SMD). ...
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1answer
21 views

Random effects, fixed effects, or perhaps nested fixed effects?

Simple question (I hope). I have the following experimental design: Two groups: A, B (let's say they represent the two sexes), where I randomly sampled 4 subjects from each group, and measured blood ...
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15 views

Unequal variance and crossed random effects in linear mixed effects model

I'm analyzing an experiment that has 50 subjects and 50 items. Each item can occur in two possible conditions. Every experimental subject produces a (continuous) response to every item, but only once ...
3
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0answers
49 views

Shall I use a random effect or not?

I need to see if in the case I am going to present it is worth to use a random effect or not. I carried out some bird counts from 9 elevated lookouts in an island. Just to orient you, these lookouts ...
3
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1answer
42 views

Under what conditions are these mixed model formulations equivalent?

I see models for "mixed effects" (i.e., models with fixed as well as random factors) specified in the literature in two ways, and I'd like to understand the conditions under which they are ...
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0answers
24 views

What is “nested” when fitting models in r?

I'd like to know what does "nested" mean when fitting a model using R. Here is a tutorial1 of the difference between "nested" and "cross". Here is another tutorial2 teaching the two way repeated ...
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1answer
116 views

Repeated measures - random effects for logistic regression in R?

Study design 504 individuals were all sampled 2 times. Once before and once after a celebration. The goal is to investigate if this event (Celebration) as well as working with animals (sheepdog) ...
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1answer
14 views

Using re.form= in predict.merMod() for a lmer() model

If I fit a model with a random-intercept and random-slope then use predict.Mermod with re.form = ~ (1|Subject), my gut told me ...
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0answers
11 views

Does cross-validation for model selection using MSPE make sense for mixed models?

Does cross-validation for model selection using mean square prediction error make sense for mixed effect models such as produced by lme4? If so, under what conditions / caveats? Also, are there any ...
2
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1answer
70 views

Fixed/Random Effects GLM for fMRI

As I understand it, this is a fixed-effects GLM (as could be used in analyzing the results of an fMRI experiment): $$Y = X\beta + \epsilon$$ I assume that $Y$ is a matrix of all the data (voxels ...
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0answers
21 views

Determining the number of operators (random effect) for a two-way chi-square test

I am designing a study to benchmark a new measurement technique with two traditional measurement techniques. Let's call the new technique N and the two traditional techniques T1 and T2. It is believed ...
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0answers
14 views

Are random slopes necessary in a counterbalanced design?

I have experimental data that includes one within-subjects factor consisting of the presentation of two different stimuli to participants. The order of the stimuli presentation was counterbalanced ...
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1answer
63 views

Nesting random effect within fixed effect using lmer() of lme4 in R

Problem I want to fit a model using the R lme4 lmer function, and I'm not sure how to specify a random effect that is nested within a fixed effect. Setup I am applying a ...
3
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1answer
29 views

random effects and clustered errors

I am running a panel model using an linear regressor. A Haussman test indicates that the random effects model is better than a fixed effects. I am also clustering the errors on country code. I would ...
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26 views

AIC / BIC alternative in random effect model

I am looking at at panel data set. Hausmann recommends using random effects modeling, I have 3 nested models and Wald believes each step to add information. However, since some of the parameters had ...
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0answers
22 views

Two-way model estimation

I have a model with 2-way fixed effects and panel data. $$y_{it}=\alpha_i+\delta_t+\beta X_{it}+ \theta D.$$ The coefficient of interest is $\theta$. (D is time dummy). I can estimate the model with ...
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1answer
39 views

Model selection for random effects: can unselected random effects be used as fixed effects?

I am working on a mixed effects model. What I would consider random effects are year, sampling transect, and sampling location. There are multiple collections taken along each transect, and multiple ...
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0answers
38 views

GEE with Mundlak-Chamberlain specification

I've only seen the Mundlak-Chamberlain (aka Mundlak aka Chamberlain* aka "correlated random effects": henceforth MC) specification applied in the random effects (RE) context. But is there any reason ...
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0answers
23 views

Same coefficients for fixed effect, random effect and OLS with panel data

I have a panel data on nonperforming loans from 1990q1 till 2014q4 with 30 banks. I would like to estimate both fixed effect and random effect model with gdp growth, unemployment, exchange rate, and ...
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1answer
52 views

Use of fixed effects and random effects

When can we do a linear regression without fixed or random effects and when do we need to use those in the regression analysis? I have tried studying a lot but have got only a vague idea. I would be ...
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0answers
22 views

Mixed model specification problem

I have an experimental design with 2 between subject factors (0 vs 1) and 7 within subject factors (7 of 28 possible levels). I measure two scale variables (Mod ...
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2answers
76 views

Fitting binomial regression model in R - correct formula, significance testing, and over-dispersion

I'm using generalized linear models to test for the effect of various predictors on some binomial data. My response is a binomial vector of successes and non-successes. I want to test whether my ...
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1answer
37 views

computing heterogeneity assigned to random factors in meta-analysis

I want to calculate the proportion of total variance in a multi-level meta-analysis with 2+ random effect terms according to pp. 1261 & equation (24) in Nakagawa & Santos 2012 ...
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19 views

Bayesian random effects

My understanding of bayesian random effects (I understand that this concept is a frequentist one, but I use it for simplicity) is that one could write down the following model: $$Y_{ij} = X_{ij}\beta ...
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11 views

bimodal random effect distribution

I'm running a generalized linear model with mixed effects and logit link function. I have fixed effects $X$ and a random effect group $G$. I'm seeing the following distribution of random effects: Is ...
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0answers
37 views

Set G in prior for MCMCglmm in R

I am new to the MCMCglmm package in R, and rather new to glm models in general. I have a dataset of species traits and whether or not they have been introduced outside of their native range. I would ...
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28 views

Case study: Testing two random effect variables separately but not together

There was a recent study published in the news, "Texting insincerely: The role of the period in text messaging." http://www.sciencedirect.com/science/article/pii/S0747563215302181 It reported the ...
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23 views

effect on time series

I have financial ratios for 13 companies for three years. In the second year all the companies issued a bond. I want to measure the effect of issuing the bond on the financial ratio results of each ...
2
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2answers
135 views

mixed effects and lme4: Do I need nesting?

I am analyzing data from a field experiment, and I am interested in the effects of fauna and altitude (fixed). Altitude has two levels, and at each site I have 5 blocks for the three levels of fauna ...
2
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1answer
73 views

Package plm random effect residuals

Simply put, I'd like to know how the plm package in R calculates the residuals of a random-effect regression. I ask this because i'm getting some "weird" outputs. Let-me reproduce them here using the ...
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1answer
64 views

How does Stata calculate the “predict varname, u” after xtreg random-effect?

What "predict varname, u" after xtreg with random-effects really do in Stata? How it works? I mean, how the ("individual") random-error component u_i is extracted from the overall e_it error ...
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17 views

OK for a random factor to be confounded with a covariate?

It frequently happens to me that I want to run a mixed model that has a covariate (like participant age) which is confounded with the random factor of participant identity. For example, I have a ...
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2answers
30 views

Can I compare and analyse the coefficients of two random effect models?

Can I compare and analyse the coefficients of two random effect models? The details of my model are below: Model 1: 2 main+ 4 controls + Time + industry dummy ...
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52 views

Fit linear model with a spatially structured random effect in R

There are n sampling units (with explicit spatial coordinates (pos_x[i], pos_y[i]), i = 1..n). Data is generated as: ...
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0answers
33 views

Interactions between random effects in mixed models

Using R and lme4 package, I've fitted the following model: ...
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0answers
20 views

GLMM for repeated longitudinal count data

I have multiple longitudinal data sets (3 repeat trials) of microbial count data for a cohort of animals (each trial had different animals); animals belonged to either a treated or untreated group and ...
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1answer
35 views

linear mixed model with 3 group categorical response

I've been looking all around the webs but cant find a conclusive answer. I have count data for a longitudinal study where subjects were grouped into three treatment groups (A,B,C) and blocked by ...
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0answers
17 views

Is random effect linear regression correct in this case?

I have an (unbalanced) individual based panel dataset and I want to estimate the predictors of total healthcare cost by looking at baseline clinical characteristics of the patients. I have data for ...
2
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1answer
42 views

Should I consider time as a fixed or random effect in GLMM?

I am attempting to determine if a type of pesticide is influencing the abundance of a particular species of bird. I have 35 years of data, which was collected along roadside survey routes that are run ...
2
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0answers
32 views

What's the difference between a random intercept and a dummy variable?

I usually work in SAS or R, so when I code a GLM with a random intercept, it's usually pretty easy. However, I've been running into a few problems (too complicated to get into here) where it might be ...
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0answers
11 views

How can the fit of a multilevel model including a new fixed effect improve if the fixed effect is not significant at all

I am trying to fit a multilevel model using the lmer package in R. My model has two levels (the upper level is "country"). I include a level 2 fixed effect (i.e., constant for each country). Here is ...
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0answers
25 views

Problem understanding linear modeling with random effects and covariates

I am new to linear modelling and I am struggling modelling random effects. I have an experiment where a group of individuals is given a drug (drug A) and another group of individuals is given a ...
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0answers
87 views

Fixed effect model

My question refers to panel data analysis. My analysis includes two different types of funds: public and private. Now I want to analyse the whole sample was well as public and private funds ...
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0answers
15 views

random effect mixture model in openBUGS

what is the command for random effect mixture model in openBUGS? in the other words, How can i do random effect mixture model in openBUGS?
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0answers
21 views

Estimating random effects model with unequal spacing by respondents

Can you estimate a random effects model when you have unequal spacing by respondents? For example, in the NLSY you can get health data in 1992, 1994, and when the respondent turns 40 which is between ...
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0answers
20 views

help with lme() for nested random effects factors [duplicate]

this is a fairly basic question, but I have spent all day trying to figure it out (including reading other questions on this page), and I could really use some help. I am trying to run a simple mixed ...