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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12 views

Why are results different from R mixed effect logistic regression models with nested random effects?

I have a dichotomous outcome on 2500 individuals. From 18 geographical areas, and many households nested within areas. I need to assess the association between various predictors and my outcome, ...
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1answer
31 views

Mixed models and longitudinal studies: Is it ok to specify a random slope with time as a categorical?

My model is currently setup as follows either with just random intercepts: ...
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24 views

Linear mixed model with two correlated dependent variables

I'm using the swissmunicipalities dataset in the package sampling of R. I consider two correlated dependent variables, the population between 40 and 65 (Pop4065), and the population aged 65 or more ...
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16 views

Using Random Effects As Independent Variables in Other Models?

I was having a discussion with a colleague yesterday about an analysis he was doing with some student achievement data. We got into a discussion of value added models (VAM), which in my understanding ...
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59 views

95% CI in nonlinear mixed-effect model {lme4} with two or more crossed random effects

I have fisheries-independent data and am interesting in estimating maturity patterns across 50 lakes that are sampled (with bias) by 4 types of gear-collections. The sampling pattern is very ...
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1answer
21 views

Random Effect Model and Response Surface Methodology

In Design and analysis of experiment , Random effect is defined as : An experimenter is frequently interested in a factor that has a large number of possible levels. If the experimenters randomly ...
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18 views

Help on calculating variance for randon mixed effects

This is related to the post here: Understanding the variance of random effects in lmer() models I'm trying to calculate that proof explicitly and am missing something. The setup is we have a random ...
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1answer
56 views

Nested random effects and interaction terms in lme4

I have a data set containing various vegetation and geomorphic variables sampled in 3 distances on both sides of 43 drainage ...
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21 views

Impute missing data for mixed effects models?

Although I will not provide a reference, because I cannot recall where I did read it, I have several times read or heard that missing data is accommodated automatically in mixed models. Can anyone ...
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1answer
343 views

Why do mixed effects models resolve dependency?

Say we're interested in how student exam grades are affected by the number of hours that those students study. To explore this relationship, we could run the following linear regression: $$ ...
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18 views

Fixed Effect vs Random Effect Output

I am currently a statistics student taking an designing experiments class. At this point I feel I am getting a good grip on when to choose between a fixed effects, random effects, and mixed effects ...
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20 views

random effect for mixed model

I have ran mixed model with random effect. I have design 4 models iteratively following Zuur et al. the simplest one, and then I have added the other main and interaction effect (all with 1|subject as ...
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20 views

Nested ANOVA with 3 random effects and unbalanced design

I would like to run a nested ANOVA to test three random effects (secteur, loc nested in secteur, site nested in loc) on the variable A. The design is unbalanced so I used lmer instead of aov. However, ...
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1answer
29 views

lmer syntax for a two-way model with one fixed and one random factor [closed]

Please could anyone tell me if my R code is correct? I have a two-way model with one fixed factor, habitat, and one random factor, site. The code I am using is: ...
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7 views

Implications of using fixed effects to account for hierarchical data structure

I am currently implementing a hidden Markov model in R, using the msm package. The data I am using are drawn from a cluster-randomized trial; i.e. there is a ...
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0answers
14 views

F test in random effects panel regression

I'm using random effects panel regression and I've 3 covariates not statistically significant and I want to test if the three parameters associated with those covariates are jointly equal to 0. Could ...
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1answer
14 views

Random Coefficient Negative Binomial Model

I have a crash count data and i want to build a random coefficient negative binomial model in R. The dependent variable will be the crash counts and covariates will be Lane width, AADT, shoulder width ...
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19 views

xtreg, re in STATA, which R2 to report? [duplicate]

After estimating the data using xtreg, re, I notice there're 3 different measures of R-squared, within, between, and overall R-2, so my question is, can I just report the overall R2 in this case since ...
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1answer
62 views

Estimates of random effects in binomial model (lme4)

I'm simulating Bernoulli trials with a random $\text{logit}\, \theta \sim {\cal N}(\text{logit}\, \theta_0, 1^2)$ between groups and then I fit the corresponding model with the ...
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16 views

Group mean centering predictors for crossed random effects

I'm fitting a mixed-effects model, in which I wish to test the effect of $X$ on $Y$, with crossed random intercepts and slopes for each subjects $S%$, and for each level of an additional grouping ...
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1answer
22 views

Using subject-specific random intercept to account for repeated measures over time

I have an epidemiologic study on subjects with yearly repeated measures on a count variable as an outcome and various yearly measured predictors. The study population changes every year somewhat, so ...
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54 views

Fixed vs. Random Effects models for binary response: Understanding “glmer” output “Correlation of Fixed Effects”

There seems to be very little explanation about the summary output obtained from the glmer package in R. To elaborate, I will start with my understanding of the Fixed Effects (FE) and Random Effects ...
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19 views
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68 views

Pooled OLS, fixed, random or mixed effects?

I am analysing a simple balanced panel data with the following variables: ...
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52 views

How can i calculate an effect size (cohen's d) from a linear random effects model (beta)

I am trying to figure out how to calculate a Cohen's d statistic for a linear random effects model. I did not do the analysis myself, I have read it in a journal article so i'm left to figure it out ...
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1answer
69 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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2answers
79 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 ...
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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, ...
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1answer
50 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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36 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 ...
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1answer
43 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 ...
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0answers
45 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 ...
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1answer
53 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 ...
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1answer
100 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: ...
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0answers
41 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
58 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 ...
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0answers
23 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 ...
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0answers
19 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 ...
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1answer
42 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 ...
2
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1answer
137 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 ...
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1answer
29 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 ...
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0answers
80 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, ...
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0answers
40 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 ...
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1answer
73 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 ...
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0answers
31 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 ...
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1answer
24 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!
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1answer
41 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 ...
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0answers
16 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 ...
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1answer
30 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 ...
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1answer
31 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 ...