As of version 0.6.0, rsimsum supports the
fully automated creation of nested loop plots (Rücker and Schwarzer,
2014).
A dataset that can be purposefully used to illustrate nested loop
plots is bundled and shipped with rsimsum:
This data set contains the results of a simulation study on survival modelling with 150 distinct data-generating mechanisms:
head(nlp)
#>   dgm  i model           b        se baseline  ss beta esigma pars
#> 1   1  1     1  0.17119413 0.2064344        E 100    0    0.1  0.5
#> 2   1  1     2  0.19822898 0.2048353        E 100    0    0.1  0.5
#> 3   1 50     2 -0.03404229 0.2071766        E 100    0    0.1  0.5
#> 4   1 82     1 -0.09263968 0.2040281        E 100    0    0.1  0.5
#> 5   1 82     2 -0.05095914 0.2026813        E 100    0    0.1  0.5
#> 6   1 33     1 -0.17013365 0.2038076        E 100    0    0.1  0.5Further information on the data could be find in the help file
(?nlp).
We can analyse this simulation study using rsimsum as
usual:
s <- rsimsum::simsum(
  data = nlp, estvarname = "b", true = 0, se = "se",
  methodvar = "model", by = c("baseline", "ss", "esigma")
)
#> 'ref' method was not specified, 1 set as the reference
s
#> Summary of a simulation study with a single estimand.
#> True value of the estimand: 0 
#> 
#> Method variable: model 
#>  Unique methods: 1, 2 
#>  Reference method: 1 
#> 
#> By factors: baseline, ss, esigma 
#> 
#> Monte Carlo standard errors were computed.Finally, a nested loop plot can be automatically produced via the
autoplot method, e.g. for bias:
However: