All Questions
22 questions
0
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1
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21
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How can I get the population variance from a mixed model?
I supposed it is a basic question, but I'm stuckle on it and I can't find the solution.
I have a date base with the slurry dry matter content from different pig production stages (CATEGORY), also, ...
- 33
4
votes
1
answer
64
views
Calculating variance of a dependent variable with multiple fixed effects
I am kind of a stats noob but I figure someone here may have some insight. I am running a linear mixed effects model in R, reminiscent of what's below:
...
- 121
1
vote
1
answer
178
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Estimation of random intercept and random slope for singleton cluster in multilevel modeling
I am performing some multilevel analyses with the R package lme4.
The study design is longitudinal with the hierachical structure of observations (L1) nested into study participants (L2). I have 215 ...
1
vote
0
answers
26
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Can slope variance be greater than ICC in lmer results
My question is can variance of the random slope be larger than random intercept variance? And if so, what would it mean in terms of group level variation?
- 11
0
votes
0
answers
26
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Linear mixed models unequeal group variances and model fit
I have data from two groups (divisions) of participants that consider attention lapses. The question is, first, do the number of attention lapses change over the two testings, and second, do the ...
- 77
2
votes
1
answer
3k
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How to get the proportion variance explained by each predictor in an lmer() model?
Is there a way to get the proportion of variance explained by individual fixed effects in a mixed effects model?
I thought that the partR2 package could do this, ...
- 2,701
1
vote
1
answer
112
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Run mixed effect model where one fixed effects shows no variation within the random factor levels
I want to run a mixed effect model to test the effect of temperature and SLA on Herbivory. In my case, the random factor is plot since my samples are nested within ...
- 11
2
votes
2
answers
248
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How to estimate proportions of variance in outcome variable attributable to each individual fixed effect variable in lmer?
I am using multivariate models in lme4 to try to work out, quantify and compare the effects on a single outcome variable of a large group of fixed effects variables. Because the data are at week and ...
- 213
0
votes
1
answer
225
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Calculating a mixed model using pdIdent var-cov matrix
I have a question in mixed models. I'm quite new at this field and I'm trying to calculate a model in which "y" is predicted according to multiple covariates (Age,gender,BMI) and the random variable "...
- 1
2
votes
0
answers
162
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How to estimate variance for identical & fraternal twins with a mixed model
I am using the twins data from OpenMx and am curious to estimate the empirical covariance structure for BMI differences in monozygous and dizygous twins:
...
- 64.8k
3
votes
1
answer
189
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How to compute correlation of random slopes for X between two Conditions with (X*Condition|subject) model in lme4?
We have the following model:
Y ~ X*Condition + (X*Condition|subject)
Y = dichotomous variable; values 0,1
X = continous variable; values ca. 0-3000
Condition ...
- 1,782
2
votes
1
answer
2k
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Partitioning variance within a level in a 3-level mixed effects model
I have a 3-level repeated measures model setup observations (level-1) nested within patients (level-2) nested within providers (level-3). One of my questions is the percentage of variance explained at ...
- 163
2
votes
0
answers
295
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Using lme4 and glmer (logit) to estimate variances of random intercepts
Our data set consists of a matrix with a few thousand respondents (rows), many items of ten surveys (columns), and all 0’s and 1’s for a certain survey answering behaviour (either responding ‘I don’t ...
- 21
0
votes
0
answers
53
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difference between estmated and empirica variance matrix of lmer random effects
Does anyone know why when I perform a lmer analysis (here using the builtin sleepstudy dataset) the estimated variance matrix of the random effects from VarCorr are so different from the variance of ...
- 360
13
votes
2
answers
5k
views
Are $R^2$ for GLMM useful for modelers but not necessarily for readers?
The short version:
1)Are there any published critiques of the use of $R^2$ for GLMMs, in particular the popular approach of Nakagawa & Schielzeth (2013) A general and simple method for obtaining $...
- 2,173
3
votes
1
answer
1k
views
Understanding variance components with an interaction structure
Suppose that I have the following dataset in R:
library(lme4)
data(Machines,package='nlme')
mydata <- Machines[Machines$Machine!='C',]
There are 3 levels with ...
- 2,769
1
vote
1
answer
3k
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How to find variance (in %) explained within the output coefficients?
I'm not very good with technical details or equations in stats as I'm quite new to running these in R. So I hope that you won't mind me asking these perhaps simple questions and also I would ...
- 105
10
votes
2
answers
7k
views
How can I test for differences in variation between groups in a mixed model (lme4)?
I would like to test for differences in variation, not in means, between two sites. By looking at a boxplot of my data I see that bird song in one site look much more variable in length than in ...
- 101
2
votes
0
answers
452
views
Multiple comparisons for variance structure in R lme fit
How can I compare variances for different levels of a factor in a mixed effect model?
I'm fitting a mixed effects model (in R using the ...
- 121
2
votes
1
answer
2k
views
Error with RLRsim package while testing for variance components
I am trying to fit the mixed effects model and test for a variance component using RLRsim package.
$$
Y_{ik} = \alpha + \mu_{k} + \beta G_{i} + Z_{k}G_{i} + b_{i} + \epsilon_{ik}
$$
Random ...
- 43
3
votes
1
answer
7k
views
Proper use of weights argument in linear mixed model [lme()]?
After attempting to produce a linear mixed model I was left with a great deal of heterogeneity.
...
- 1,193
9
votes
1
answer
999
views
What to do with heterogeneity of variance when spread decreases with larger fitted values
I am trying to produce a linear mixed model the R code is as follows.
lme(Average.payoff~Game+Type+Others.Type+Game:Type+Game:Others.Type+Type:Others.Type,random=~1|Subjects,method="REML", data=...
- 1,193