New answers tagged lme4-nlme
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How can I get the population variance from a mixed model?
In a mixed-effects model, the standard errors of the fixed effects are not the equivalent of the mean squared error (mixed squares). The standard errors quantify the uncertainty in estimating the ...
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Calculate inter-rater noise using Kahneman et al. (2021) approach
I too find the analysis of noise, described by Kahneman, Sibony and Sunstein in Noise: A Flaw in Human Judgment, idiosyncratic. Here's my attempt at understanding their calculation.
In Chapter 6, ...
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Fitting a Nonlinear Mixed Model
I would recommend using a Generalized Additive Model (GAM) for this data. You can find a great introduction to GAMs here. I would encourage going through the link to understand what GAMs are prior to ...
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nlme ignoring certain control arguments to nlminb
Unfortunately, it has been 6 years, and still no way to constraint parameters for nlme.
Unless there is a way I am unaware of but for now transformations seem to be the only work around.Either that or ...
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R: How to fit a linear mixed model with a custom covariance structure for two random intercepts
Since each $(b_{1j}, b_{2j})$ (independently) follows the same bivariate normal distribution for $j \in \{1, \ldots, q\},$ your model is observationally equivalent (in the sense of an identical ...
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R: How to fit a linear mixed model with a custom covariance structure for two random intercepts
To fit your linear mixed model (LMM) with the desired covariance structure for the random effects in R, you’ll need to use a package that allows specification of the covariance structure explicitly. ...
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Modelling a binary outcome when census interval varies
This question fits in the field of discrete survival data and analysis.
The role of offset() is to enforce whatever inside to have a coefficient exactly at 1 with ...
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Estimating mixed model with identical response value but different covariate values within a pair
Depending on what question you are trying to answer, there's a different modeling approach I would consider. It has the following idea:
Every individual has a certain skill at the task. If they are ...
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How to change variance-covariance matrix in mixed models?
In general the simr package takes a fitted model as input, so I'm not quite sure why you don't just pass m_pilot to ...
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If the categorical variable is retained in my final model in R, then why does the post hoc analysis say the levels do not differ?
There are two things going on:
You may have a lot of fish, but the experimental units for category.of.urbanization are the rivers, not the fish. For that reason, ...
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Repeated measures within participant
In addition to my general answer on the distinction between random effects and correlated residuals, a practical example follows using the classical reaction-time data and the R package {nlme}. For a ...
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LMEM - When is it okay to not treat repeated measures as a random effect? And other related questions
Much of your question is covered in the answers to this question. If you don't have enough observations, you will end up with problems like yours when you try to fit a complex random-effects structure ...
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lmerMod vs lmerModLmerTest - what are the differences and which is correct?
ChatGPT is simply making up numbers.
lmerTest provides a wrapper around lme4 which provides denominator degrees-of-freedom ...
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Is setting a certain covariance structure between random effects and zeroing R equivalent to setting this structure exclusively in residual matrix?
Dimitris Rizopoulos's answer is incorrect. glmmTMB(cs(0 + factor | ID)) is not the same as ...
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