## Dataset

Unfortunately, I posted this question on cross-validated and have yet to get an answer (see here).

I am working on a dataset collected from more than 20 hospitals. I used the `glmer`

command to estimate a mixed-effects logistic regression model with the following as patient-level predictors:

- age (patient’s age; a continuous variable),
- cci (Charlson Comorbidity Index; a continuous variable),
- sex (patient’s sex; man vs. woman),
- race (patient’s race; Asian vs. Black vs. South Asian vs. White), and
- htn (has hypertension vs. no hypertension).

I used the hospital variable (the hospital that recruited patients) to estimate the random intercept.

## Problem

**My code for mixed-model (worked very smoothly):**

`mixed_died30in <- glmer(died30in ~ age + cci + sex + race + htn + infx_source + (1 | hospital), data = passem, family = binomial, control = glmerControl(optimizer = "Nelder_Mead"), nAGQ = 10)`

**Then I used the mfp command:**

`mfp_died30in <- mfp(glmer(died30in ~ fp(age, df = 4, select = 0.05) + fp(cci, df = 4, select = 0.05) + sex + race + htn + infx_source + (1 | hospital), family = binomial, data = passem, control = glmerControl(optimizer = "Nelder_Mead"), nAGQ = 10))`

**The following error appeared:**

```
Error in fixed.only && random.only : invalid 'x' type in 'x && y'
In addition: Warning message:
In checkConv(attr(opt, "derivs"), opt$par, ctrl = control$checkConv, :
Model is nearly unidentifiable: large eigenvalue ratio
- Rescale variables?
```

## Questions

- Does the
`mfp`

command from the mfp package in R support mixed-effect models? - Is (are) there any problem(s) in my code?

Any help would be so appreciated

Abdullah