inconsistent behavior with `mclogit` objects

[IndrajeetPatil]

broom currently doesn't support mclogit objects. But because these objects also inherit lm, the tidier seems to work.

# setup
set.seed(123)
library(mclogit)
#> Loading required package: Matrix
data(electors)

# model
mod <- mclogit::mclogit(
  formula = cbind(Freq, interaction(time, class)) ~ econ.left / class + welfare / class + auth / class,
  random = ~ 1 | party.time,
  data = within(electors, party.time <- interaction(party, time))
)
#> Fitting plain conditional logit to obtain starting values
#> Iteration 1 - Deviance = 7377.939
#> Iteration 2 - Deviance = 4589.544
#> Iteration 3 - Deviance = 4293.485
#> Iteration 4 - Deviance = 4277.887
#> Iteration 5 - Deviance = 4277.808
#> Iteration 6 - Deviance = 4277.808
#> converged
#> Fitting random effects/random coefficients model
#> Iteration 1 - Deviance = 1876.788
#> Iteration 2 - Deviance = 1212.004
#> Iteration 3 - Deviance = 1009.8
#> Iteration 4 - Deviance = 958.7431
#> Iteration 5 - Deviance = 949.4332
#> Iteration 6 - Deviance = 948.1453
#> Iteration 7 - Deviance = 947.9013
#> Iteration 8 - Deviance = 947.8442
#> Iteration 9 - Deviance = 947.8329
#> Iteration 10 - Deviance = 947.8308
#> Iteration 11 - Deviance = 947.8305
#> Iteration 12 - Deviance = 947.8304
#> Iteration 13 - Deviance = 947.8304
#> Iteration 14 - Deviance = 947.8304
#> converged

# class of objects
class(mod)
#> [1] "mmclogit" "mclogit"  "lm"

# tidier?
broom::tidy(mod)
#> # A tibble: 9 x 5
#>   term                      estimate std.error statistic   p.value
#>   <chr>                        <dbl>     <dbl>     <dbl>     <dbl>
#> 1 econ.left                  -0.172     0.138     -1.25  2.12e-  1
#> 2 welfare                     2.05      0.214      9.58  9.71e- 22
#> 3 auth                        0.0817    0.118      0.691 4.89e-  1
#> 4 econ.left:classnew.middle  -1.67      0.0880   -19.0   3.61e- 80
#> 5 econ.left:classold.middle  -2.97      0.149    -19.9   4.56e- 88
#> 6 classnew.middle:welfare    -0.989     0.0609   -16.2   2.30e- 59
#> 7 classold.middle:welfare    -1.62      0.129    -12.6   3.82e- 36
#> 8 classnew.middle:auth       -1.39      0.0468   -29.8   1.64e-194
#> 9 classold.middle:auth        1.46      0.0582    25.0   2.05e-138

But it has trouble computing confidence intervals because the underlying method from stats fails:

# confidence intervals?
broom::tidy(mod, conf.int = TRUE)
#> Error in qt(a, object$df.residual): Non-numeric argument to mathematical function

# is there even a method for this?
confint(mod)
#> Error in qt(a, object$df.residual): Non-numeric argument to mathematical function

The glance and augment methods also fail:

# glance?
broom::glance(mod)
#> Error in eval_tidy(xs[[i]], unique_output): object 'r.squared' not found

# augment?
broom::augment(mod, data = electors)
#> Error: Can't augment data with observation level measures.
#> Did you provide `data` with the exact data used for model fitting?

^{Created on 2019-08-09 by the reprex package (v0.3.0)}

Session info

devtools::session_info()
#> - Session info ----------------------------------------------------------
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#>  date     2019-08-09                  
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[alexpghayes]

Another case where the short term solution is

#' @export
tidy.mclogit <- tidy.default

...

and the long term solution is new tidiers. GAH WHY DOES EVERYONE SUBCLASS LM.

[IndrajeetPatil]

Closing following #795 (comment)

[github-actions]

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