Apologies in advance because I think this is likely to be user error! I’m trying to extract the grand mean from a model by using ‘NA’ within the newdata argument of fitted(), as described here in the documentation:

`NA`

values within factors in`newdata`

, are interpreted as if all dummy variables of this factor are zero. This allows, for instance, to make predictions of the grand mean when using sum coding.

From: https://www.rdocumentation.org/packages/brms/versions/2.10.0/topics/fitted.brmsfit

However, when I use NA within a factor, I’m getting an error:

‘Error in X %*% re$trans.U : non-conformable arguments’

My model is:

```
brm(
bf(
y ~ main + indicator_var * log_inv_logit(interaction),
main ~ offset(log_dilution) + factor2 -1,
interaction ~ s(x, bs = 'gp') +
s(x, by = factor1, bs = 'gp') +
s(factor1, bs = "re") +
(1|factor2),
nl = T
),
data = as.data.frame(data),
family = poisson(),
prior = priors,
iter = 5000, warmup = 2500, chains = 4, cores = 4,
silent = F
)
```

Reproducible example below:

```
# setting up data
factor1 <- rep(c(rep("A",6), rep("B",6), rep("C",6)), 2)
set.seed(42)
data <- data.frame(
factor1 = factor(as.character(factor1)),
factor2 = factor(as.character(c(seq(1,18)), seq(1,18))),
indicator_var = c(rep(1, 18), rep(0, 18)),
log_dilution = c(rep(log(1), 18), rep(log(0.1), 18)),
x = as.double(c(seq(1,18), seq(1,18))),
y = c(round(runif(18, min = 0, max = 100)), round(runif(18, min = 10, max = 100)))
)
# priors
priors <- c(
set_prior('normal(0, 100)', class = 'b', nlpar = 'main'),
set_prior('normal(0, 100)', class = 'b', nlpar = 'interaction')
)
# model
spline_fit <- brm(
bf(
y ~ main + indicator_var * log_inv_logit(interaction),
main ~ offset(log_dilution) + factor2 -1,
interaction ~ s(x, bs = 'gp') +
s(x, by = factor1, bs = 'gp') +
s(factor1, bs = "re") +
(1|factor2),
nl = T
),
data = as.data.frame(data),
family = poisson(),
prior = priors,
iter = 5000, warmup = 2500, chains = 4, cores = 4,
silent = F
)
# making newdata, removing y and replacing factor1 with NA to get grand mean
my_newdata <- data %>%
select(-y, -factor1) %>%
mutate(factor1 = as.factor(NA))
#using fitted
fitted(spline_fit,
newdata = my_newdata,
re_formula = NULL,
nlpar = "interaction",
summary = T, probs = c(0.05, 0.95),
allow_new_levels=TRUE)
```

Without using NA in the new data, I’m getting sensible results for the splines from each group of ‘factor1’. But what I’d also like to extract fitted values for is the “s(x, bs = ‘gp’)” spline. I get the same error with ‘predict’.

- Operating System: Windows 10
- brms Version: 2.11.0

Thanks in advance!