# Tag Info

### Why does centering predictors resolve non-convergence in lme4?

I doubt that centering your predictors will have much of an effect on convergence in itself. What may help in some cases is rescaling. The combination of the two operations is usually called '...
• 3,658

### Random effect variance with or without fixed-effects intercept

I agree with @Roland's comment. What values does SAM_Aro take? Keep in mind that the mean of both sets of random intercepts (participant and video) is, by ...
• 2,672

### Model Convergence after R Crash. (Warning: Model failed to converge with max|grad| = 0.00247628 (tol = 0.002, component 1))

Without knowing anything else about how you obtain the subsets of your full data to generate df1 or df2, I can only speculate. If you randomly subsample from the full data set without fixing a seed ...
• 121

### When analysing time series data with lme4, how do you include both a step-change and a slope-change?

Your model currently has a single fixed time parameter, which is the same for all observations. The estimate is very slightly negative, so all your predictions ...
• 3,658

### Random intercept

That's a very interesting model ! I'm curious about what kind of data you are dealing with, and your research questions? Anyway in nlme you can usually just specify ...
• 59.8k

### lme4: adding covariates and interpreting output

I hope this helps: Question 1: This is code assuming you have 3 predictors (pred1, pred2, pred3). A'covariate' is just treated the same as other predictors in the code. I use 'Response' as your ...
• 472
Accepted

### Error: PIRLS loop resulted in NaN value in GLMM (glmer) model with Gamma distribution

One of the key assumptions of using linear regression techniques is that the modeled relationship is linear. Plotting your data it seems that at least for ...
• 5,826
Accepted

### Specifying a model with random effects for a strip-plot designed experiment in R

Let's name the models under consideration for ease of reference. Using R's formula notation: ...
• 9,550

### nlme estimates near zero variance for the random effects

As others have pointed out, the problem is singularity that the estimated variance of random intercepts is at its boundary zero. In such cases, lme4 prints messages ...
• 1,325
Accepted

### ANOVA, ANCOVA, linear mixed effect model

Option 1 and 2 are a no-go because your observations are clearly non-independent given the repeated measures. Option 3 looks the best to me. I prefer using lme4 for ...

### Modeling repeated measures data in R - Interpretation and Validation

To help make your original regression results more interpretable, I suggest that you code timepoint such that the first occasion is given a value of 0. This is because in regression models, the ...
• 4,582
1 vote

### Rank deficiency and interaction term not estimated

The problem is in the design; you don't really have 2x2, you have something like 2x1.5. Whenever there is high lexical complexity, there is average readability, so the interaction can't be estimated. ...
• 117k

### Mixed model in lme4 package is singular

As reported there are many reasons for singularity. Your example is not reproducible for the lack of data. Could you provide some characteristics of the data e.g. the levels of each factors and the ...
• 11
Accepted

### Cautions or considerations when setting coefficients from linear model into the fixed-effects component of a mixed effects model

Note that to estimate the random effect, you need the fixed effects and the variance components. In particular, for a random intercepts model, the formula is \hat{b}_i = \frac{n_i \sigma_b^2}{\sigma^...
• 20.8k

### How to add interaction and covariates to linear mixed effects model in R

Fixed/Random Variable Inputs There's nothing stopping you from adding any number of variables that were measured at baseline. If this measure was also repeated, then you would need to code that into ...
Accepted

### Interpretation of Intercept in mixed model with repeated contrasts

To make an attempt at answering my own question... I believe that the intercept here is indeed the mean (log likelihood) of Response=1 across all conditions. The p-value for the intercept tests ...
• 472
1 vote

### Correlations Fixed Effect

Your assumption of multi-collinearity is correct, but it's not necessary for multi-collinearity that a*c and a*b are correlated ...
• 2,044
Accepted

### Solutions to a 'singular fit' in generalized linear mixed-effects models

Solutions Here are some common solutions to singular fits, some of which are listed in the help function listed in the error call for glmer... The most common ...
Accepted

### How to interpret the output of 'Linear mixed model fit by REML' in R?

It's not clear what vnr is here, but I will answer in a general sense what your output is saying. First I start with some less important bits. Formula: This is ...