find_formula struggles with few model objects

[IndrajeetPatil]

# model-1
library(car) 
#> Loading required package: carData
mod <- stats::lm(
  formula = conformity ~ fcategory * partner.status,
  data = Moore,
  contrasts = list(fcategory = contr.sum, partner.status = contr.sum)
)

# random-effects
insight::find_random(car::Anova(mod, type = "III"))
#> Error in find_formula.data.frame(x): A data frame is no valid object for this function



# model-2
library(lme4)
#> Loading required package: Matrix
#> Registered S3 methods overwritten by 'lme4':
#>   method                          from
#>   cooks.distance.influence.merMod car 
#>   influence.merMod                car 
#>   dfbeta.influence.merMod         car 
#>   dfbetas.influence.merMod        car
set.seed(123)
startvec <- c(Asym = 200, xmid = 725, scal = 350)
nm1 <- lme4::nlmer(circumference ~ SSlogis(age, Asym, xmid, scal) ~ Asym | Tree,
                   Orange,
                   start = startvec
)

# random-effects
insight::find_random(nm1)
#> Error in reformulate(attr(termobj, "term.labels")[-dropx], response = if (keep.response) termobj[[2L]], : 'termlabels' must be a character vector of length at least one

^{Created on 2019-09-16 by the reprex package (v0.3.0)}

Session info

devtools::session_info()
#> - Session info ----------------------------------------------------------
#>  setting  value                       
#>  version  R version 3.6.1 (2019-07-05)
#>  os       Windows 10 x64              
#>  system   x86_64, mingw32             
#>  ui       RTerm                       
#>  language (EN)                        
#>  collate  English_United States.1252  
#>  ctype    English_United States.1252  
#>  tz       Europe/Berlin               
#>  date     2019-09-16                  
#> 
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[IndrajeetPatil]

@strengejacke Do you think this bug can be fixed before the next CRAN submission?
I want to use this function in my package but been waiting for this to be fixed.

[strengejacke]

I can look at this, there is no hurry for insight to be released, I think.

[strengejacke]

related to #66

[strengejacke]

two things:

1. car::Anova() returns a data frame, and I don't see how to get any information about the underlying model object.

2. nlmer() only works with included fixed effects when the random effect term is written in classical lmer-style, i.e. circumference ~ SSlogis(age, Asym, xmid, scal) ~ x1 + x2 + (Asym | Tree).

[IndrajeetPatil]

Thanks for fixing this so quickly!

[strengejacke]

The 2nd point can be blamed to the lmee-package, because findbars() doesn't work properly here:

library(lme4)
#> Loading required package: Matrix
data("Orange")

Orange$x1 <- runif(nrow(Orange))
Orange$x2 <- rnorm(nrow(Orange))

set.seed(123)
startvec <- c(Asym = 200, xmid = 725, scal = 350)

m1 <- lme4::nlmer(
  circumference ~ SSlogis(age, Asym, xmid, scal) ~ x1 + x2 + Asym | Tree,
  Orange,
  start = startvec
)

m2 <- lme4::nlmer(
  circumference ~ SSlogis(age, Asym, xmid, scal) ~ x1 + x2 + (Asym | Tree),
  Orange,
  start = startvec
)

lme4::findbars(formula(m1))
#> [[1]]
#> x1 + x2 + Asym | Tree
lme4::findbars(formula(m2))
#> [[1]]
#> Asym | Tree

^{Created on 2019-10-17 by the reprex package (v0.3.0)}

[IndrajeetPatil]

Maybe we can raise an issue on lme4's GitHub repo?

[strengejacke]

Yes, I did already.