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4 votes
1 answer
171 views

minimum amount of prior to get a mixed-model to converge (in R)

This may be a simple/naive question, but I have a non-converging lmer() model due to singularity of its random covariance matrix. I was wondering what is a possible ...
rnorouzian's user avatar
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2 votes
0 answers
130 views

How to model a multiplicative effect of a parameter

I am having difficulty in fitting a model on data. Basically, I have data about the evaluation of phenotypic property (i.e. hard) of 65 palm trees by 5 judges. As an evaluation scheme, each judge ...
maddy's user avatar
  • 21
1 vote
0 answers
51 views

Opposite results using Bayesian (STAN) vs Multilevel model (nlme). How is this possible?

My datasets contains the median wages and the cumulative installed wind-capacity for 4000 counties over a period of 20 years. The wages tend to rise over the period and the capacity tends to highly ...
user442239's user avatar
1 vote
1 answer
33 views

Determining the number of interactions between the independent variables

I am trying to use GLMMs models to analysis the morbidity status of child (yes or no) with mother’s demographic and environmental factors like Wealth with factors ("Lower quartiles”,"...
Sofonias Derso's user avatar
1 vote
0 answers
47 views

Variance of random effects in lmer output

Consider this simple simulated dataset (all groups are normally distributed with sd=1) made up by 4 level 1 groups (lv1) and 2 level 2 groups. The mean of the 4 distribution is 5, 15, 5 and 15 ...
Mirko's user avatar
  • 133
1 vote
0 answers
173 views

Equivalency of regularization among LME, Bayesian and penalized least squares

Suppose that we have a linear mixed-effects (LME) model $\boldsymbol{y}=X\boldsymbol{\beta} + Z\boldsymbol{u} + \epsilon$ where $y$ is an $n \times 1$ vector of responses and $X$ and $Z$ are design ...
bluepole's user avatar
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