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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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6 views

Difference between random effect and fixed effect with regularization/prior

Let's say I have a random effect intercept. For example: lmer(yield ~ 1 + (1|Batch)) How is that different than just ordinary regression using regularization or ...
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0answers
12 views

Interpreting interacting random effects in lme4

My questions is about how to interpret the output from lme4 for interacting random effects. Our model is as follows: ...
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0answers
11 views

Negative value when Calculating variance in population mean [on hold]

I am following the Hunter-Schmidt method for a meta analysis of Pearson r values. I am wondering if there is a way in which to create 95 % credibility intervals when I have a negative value for ...
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0answers
16 views

random intercept, random slope plus intercept, no random slope alone?

I measured running speed of 70 individual lizards. The lizards were siblings born of 7 mothers, 10 offspring each. The Lizards ran at 3 different temperatures, A, B, and C, where A < B < C, and ...
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0answers
9 views

In R, compute ICC(A,1) for two way mixed effects model [on hold]

I want to compute ICC(A,1) defined by McGraw and Wong (1996). It a single score, absolute agreement, two-way mixed effects model. Is there a function in R that can calculate this? I have looked at ...
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0answers
10 views

Random intercept and slopes structure from lmer to lme in R [closed]

I want to make this model (from lmer) but using lme and I cannot figure out how to set up the random structure! This is the structure using lmer: lmer(Tempcnt ~ Yearcnt + (1|site) + (0 + Yearcnt|...
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0answers
21 views

Random effects in gamlss

I have a question regarding the gamlss package. I am attempting to fit a mixed effects model using the Befa Inflated distribution as follows ...
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0answers
5 views

Longitudinal data Random effect of time 0 - meaning?

I have longitudinal data collected at three waves (in 2004, 2007 and 2011). The three waves have decreasing sample size, because is a follow up cohort study. I am interested in investigating the ...
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1answer
37 views

Understanding whether to use two-way effects [duplicate]

Using plmtest, I find that individual effects are significant (p: 7.327e-05); time effects are not significant (p: 0.1263); and two-way effects are significant (p: 0.0001197). Based on these results,...
3
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1answer
23 views

How does pooling work with crossed effects in multilevel models?

In Section 12.2 of Gelman and Hill, The authors mention that one of the main benefits of creating a multi-level model is that you can take advantage of "partial pooling". As an example, if you were ...
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0answers
29 views

Random repeated-measures linear mixed-effect model

I want to analyze how the number of ants of the species "A" is related to different environmental measurements (Temperature, relative humidity, and wind speed), number of flowers, number of ...
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1answer
18 views
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0answers
21 views

When is it OK to calculate the AUC for a mixed-effects logistic regression model without the random intercept?

I fit a mixed-effects logistic regression model in R with glmer. There is one dependent variable, one dichotomous predictor variable, and one random intercept. The ...
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0answers
7 views

Theory about LMM -design matrices for nested and crossed effects

I want to explore the details of the design matrices involved in Linear Mixed Models (LMM) with random effects associated with crossed and nested grouping factors. Of great interest to me, is also, ...
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0answers
30 views

Shared frailty model: frailty (random effect) correlated with independent variable WITHIN groups - a problem or not?

Dear CrossValidated community, Background: I would like to estimate a shared frailty model (see these lecture notes; the following draws on this document). It is a a random effects survival analysis ...
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0answers
8 views

lme4 How to interpret a random slope effec while there is no fixed effect?

I have a question regarding the interpretation of multi-level models. This is my first model: m1 = lmer(Y ~ x1 + x2 +(1| class), REML = FALSE, data=dataset) In ...
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1answer
45 views

Linear mixed-effects model equation for correlated and uncorrelated random slopes

I've been asked to provide a linear equation for a lme4:lmer() model that I report in one paper. I tried to adapt examples from http://rpsychologist.com/r-guide-...
2
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1answer
36 views

Can a random slope in a linear mixed model mask the effect of my intervention?

I want to assess the impact of my intervention in a repeated-measures design. I have subject as a random intercept in order to account for the dependence of measurements within subjects: ...
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0answers
20 views

Multi-level Models - Date as a Random Effect

Hi I was wondering if someone would be able to help me decide on the proper set up for a multi-level model using the lmer package. In my study, we are looking at heart rate in beats per minute ...
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0answers
8 views

Should geographic location always be included as a random model effect?

Under what sort of experimental conditions and/or objectives might someone be justified in modeling geographical location as a fixed effect (assuming that most times location is included as a random ...
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0answers
8 views

how are variance components for random effects calculated for mixed model when the effect is categorical?

I have a question about how variance components are calculated for categorical variables in mixed models. For example I have a cluster vector of (4, 4, 6, 6, 5). If the overall mean is 6, then the ...
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0answers
13 views

Have I adjusted for predictors I use as random effects?

I believe this is a rather straight forward question. I just read a research article in which it stated that: "[...] we used study centre as random effect, which also means that we adjusted for study ...
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0answers
31 views

Trying to understand a latent curve model in terms of mixed effects regression

I'm trying to understand exactly what the following model is trying to represent: (taken from Beaujean's Latent Variable Modeling Using R book) The text indicates that this is a random intercept/...
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1answer
74 views

OLS, Fixed effects or Random effects Model?

I am a little bit confused about type of model to apply because my type of data. I am interesting in get regression parameters for time (dependent variable) with independent variables= sex + age+ ...
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0answers
15 views

Calculating proportion of variance explained by random effect in multinomial GLMM

I have a multinomial logistic GLMM with one random intercept. The number of response categories $C = 4$. Since a multinomial logit model consists of $C-1$ binomial logit models -- each pairing one non-...
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1answer
22 views

Random generation of wealth with normal distribution of two parameters? [duplicate]

I want to randomly generate the wealth of a group of people, with two parameters: age and height. Basically (not necessarily realistic): Rule 1. the older a person (allow decimals), the higher the ...
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0answers
38 views

running simple glmer (NULL) model returns warning message -R

I am running a simple model: ...
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0answers
10 views

¿Any suggestions? GLM, HLM, MLM Problem (lme4)

I'm new to Multilevel modeling and currently I been working on a business project and its data is related to multilevel modeling. I know a lot of things about how to approach this problem, but I will ...
2
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0answers
27 views

ANOVA for difference of means - is there a random effect due to population sampling?

I would like to know if a population sampling "random effect" applies in a very simple difference-of-means test. CASE 1: A toy scenario to setup the question: suppose we want to compare the ...
1
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1answer
38 views

Why are the coefficients of REML and ML estimation the same? What does that mean?

I have estimated a linear mixed model with REML and ML estimation. However, the estimated coefficients do not differ. The standard errors of the coefficients are slightly higher for the REML ...
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0answers
5 views

Question on options in Bayesian random effects models MCMChregress function

Maybe I am missing something fundamental but I am wondering what the r and R options in the MCMChregress function change the performance of the model and what might be some techniques to find the best ...
2
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0answers
111 views

lmer: number of grouping levels < number of observations

Error: number of levels of each grouping factor must be < number of observations This is a common error when using the lme4 package, and there are a number of questions about it on cross validated ...
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0answers
34 views

same variable as both random and fixed effect in mixed models

Let's say I have a variable with 6 levels, for example, different tasks which are just a subset of all possible tasks. I am interested in differences between the tasks so should add it as a fixed ...
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0answers
42 views

is it correct to nest fixed effects within random factors?

In this post @Ben Bolker wrote in his answer that for the interaction between station and day we could write ...
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2answers
88 views

Alternatives for random effects anova

We have an experiment that seeks to establish a particular continuous quantity as a possible objective indicator of some subjective categories. Since we cannot share the particular experiment (company ...
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1answer
31 views

SAS proc mixed Degree of freedom

I have a dataset in this format: Factor A is a between subject factor (with 2 levels - High and Low). Factor B is a within subject factor (with 3 levels - High , Moderate and Low). I want to run a ...
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0answers
45 views

Anyone familiar with Tobit panel models w/ random effects (and Stata's xttobit and metobit)?

I am not an expert when it comes to econometrics but I find myself in need of carrying out an empirical analysis. My question pertains to how exactly I might (or should) go about specifying the random ...
3
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0answers
11 views

Estimating within group variability given high uncertainty

Suppose we have products $P_i$ $(i=1,2,\cdots,N)$. Each product has three different descriptions, which we denote by $(X_{ij},y_{ij})$ for $j\in \{1,2,3\}$, where $X_{ij}$ are the description features,...
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0answers
5 views

Crossed random effects with censored response?

Is there some way to do regression on a computer (preferably in R, but I'm willing to try out other software as long as it's something I can find access to) with a censored response and crossed random ...
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0answers
9 views

Fitting a single-level model with group-level predictors (No random effects)

can someone explain me this affirmation. "High risk of Type I errors because standard errors of coefficients of group-level predictors may be severely underestimated. No estimate of the between-group ...
2
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0answers
23 views

Adjust for variable in mixed effects model

I've looked at prior posts as well as the lme4 documentation in R but can't seem to find a solution to my problem. I am trying to model how an intervention (tutoring), impacts examination pass rates ...
2
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0answers
32 views

Wikipedia says that “The random effects model is a special case of the fixed effects model”. Why?

I understand that the assumption made in a fixed effects model is that there is a basic understanding of the included parameters, e.g. there is a proven theory or previous experiments have shown non-...
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0answers
8 views

“inconsistent” predicted random effects in nlme

I am learning the linear mixed-effect models and have trouble figuring out the predicted random effects. I found differences between fixed and ...
1
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1answer
44 views

Is a linear mixed-effects model appropriate for my nested dataset?

I'm not entirely confident in the statistical method I am using for my study design, and would like some feedback/advice. I am primarily looking at the effect of land use on stream chemistry ...
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0answers
16 views

Which regression model in appropriate when dependent variables are at individual level and independent variables at national level?

This is actually a panel data where dependent variables are in binary figures y1 ... y4 exhibiting thousands of entries for a single country. On the other hand few independent variables are on the ...
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0answers
21 views

HLM, MLM, LMM: How to approach this problem? (in R)

I'm trying to do a HLM analysis on a current project. Basically is data collected from surveys where each person gives a "grade" (as integer) to an specific business X. Also, this business belongs to ...
7
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1answer
116 views

The mathematical representation of a nested random effect term

Suppose that a dependent level variable $y$ is measured at a unit level (level 1) that is nested within units of type $A$ (level $2$), and that units of type $A$ are nested within levels of type $B$ (...
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0answers
35 views

Accountng for variance through random effects in a mixed model

I am working with a rather large data set (over 500 subjects) that has been scored/coded for multiple different variables. This particular data set is a longitudinal analysis (with 4 time points) of ...
2
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0answers
16 views

Ability of fixed-effects analyses to enable generalisation of results

Is it correct to say that, when making inferrence on the results of an experiment, using a random-effects (RFX) rather than a fixed-effects (FFX) model merely makes the results more generalisable, as ...
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0answers
20 views

What is the difference between random effect and multilevel (or mixed effect) models? [duplicate]

Multilevel models with with random intercept seem to perfectly correspond to a random effect model (in the econometric terminology). I suspect that the two concepts are essentially overlapping, ...