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68 views

I am finding the nrounds that the cross validation for xgboost returns are highly variable. This of course translates to models with varying performance. This is especially a problem when I compare ...
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1 answer
53 views

I am currently looking at country-wide population ‘censuses’ that were conducted by feeding vultures at all restaurant sites simultaneously. Simultaneous census counts were conducted twice in June ...
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1 answer
175 views

I would like to compare a pair of non-nested models that I fit using lme4 in R. I would like to apply the Vuong test (1989) for that. It seems like the nonnest2 package is the only one that supports ...
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1 answer
529 views

I am doing some model comparison with a glmer fit with lme4. My global model has 4 fixed effects and 1 random effect, plus interactions between 3 of the fixed effects: response ~ a + b * c * d + (1|e) ...
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114 views

Any suggestions on how to best implement a power analysis in R when having a binomial generalized linear mixed model (glmm) with 2 categorical predictors as fixed effects (2 levels and 8 factor levels)...
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1 answer
115 views

I have two strict non-nested models that I would like to compare. However, the normal distribution assumption is violated, so the models were calculated with a robust estimator (MLR).
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1 answer
2k views

We are performing a beta mixed-effects regression analysis using glmmTMB package, as shown below: mod = glmmTMB::glmmTMB(data = data, formula = rating ~ par1 + par2 + par3 + ...
4 votes
0 answers
679 views

I am trying to make a model comparison (say, for hypothesis testing) of two GAMs (mgcv package), where both models include random effects smooth term (s(bs="re")), and the second model ...
1 vote
2 answers
667 views

I am fitting several mixed models using the lmer function in the package lme4, each with the same fixed effects and random effects, but different response variables. The purpose of these models is to ...
0 votes
1 answer
530 views

I have a model with several main effects and several interactions. I want to avoid any models that would only include the 3 interaction terms. So basically all variations of main effects and main ...
0 votes
0 answers
437 views

I want to test if model_1 <- feols(auth ~ dummy_past1 + dummy_past2 + dummy_past3 | region + date_f, # Fixed Effects data=df) is just as good as model_2 <- feols(auth ~ i(dummy_past1,...
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149 views

I am new to R and lmer. We have a project examining the effects of mimicking others’ voice (mimicry vs nonmimicry, a between-subjects fixed effect) , modality (reading vs listening, a within-subjects ...
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0 answers
110 views

I'd like some insight on a couple of topics :"EMF compare" and "model to model comparison" in general. I am trying to achieve a comparison between two XMI models, which are ...
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1 answer
436 views

I want to know if the development of volume over time (and I mean age, not waves) is different between groups. I also have some covariates. I made a simulation dataset: library(simstudy) def <- ...
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1 answer
1k views

I'm new to deep learning so if the question doesn't make sense plz correct me. In traditional machine learning I know how to compare models and choose one of the as the best with the metrics I choose. ...

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