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Tables of a transition-model enumeration

Source: R/lta-compare.R
get_results.latents_transition_enumeration.Rd

The result of enumerate_classes(..., time = ): one transition model per number of profiles and group classes (and covariance structure, when model names several).

Usage

# S3 method for class 'latents_transition_enumeration'
get_results(
  x,
  what = c("candidates", "best"),
  criterion = c("bic", "aic", "bic_individual"),
  ...
)

# S3 method for class 'latents_transition_enumeration'
as.data.frame(x, row.names = NULL, optional = FALSE, ...)

# S3 method for class 'latents_transition_enumeration'
print(x, ...)

# S3 method for class 'latents_transition_enumeration'
summary(object, ...)

Arguments

x

A latents_transition_enumeration result.

what

"candidates" (one row per candidate) or "best" (the lowest value of criterion).

criterion

"bic" (penalized by the number of groups), "aic" or "bic_individual".

...

Unused.

row.names, optional

Unused; part of the generic.

object

A latents_transition_enumeration result.

Value

A base data.frame, one row per candidate: n_profiles, n_group_classes, model, log_likelihood, n_parameters, aic, bic, bic_individual, relative profile entropy, converged, boundary, n_best_replicated, warnings and error.

Examples

# The first 50 students keep the example quick
few_students <- subset(course_engagement, student <= 50)
grid <- enumerate_classes(few_students, c("browse", "lectures"),
                          "student", time = "sequence", n_profiles = 2:3,
                          n_group_classes = 1, n_starts = 2, seed = 1)
get_results(grid)
#>   n_profiles n_group_classes model log_likelihood n_parameters      aic
#> 1          2               1  <NA>      -1799.274           11 3620.548
#> 2          3               1  <NA>      -1790.352           20 3620.704
#>        bic bic_individual   entropy converged boundary n_best_replicated
#> 1 3641.580       3670.258 0.7752585      TRUE    FALSE                 2
#> 2 3658.944       3711.087 0.7016252      TRUE    FALSE                 2
#>   warnings error
#> 1           <NA>
#> 2           <NA>
get_results(grid, "best")
#>   n_profiles n_group_classes model log_likelihood n_parameters      aic     bic
#> 1          2               1  <NA>      -1799.274           11 3620.548 3641.58
#>   bic_individual   entropy converged boundary n_best_replicated warnings error
#> 1       3670.258 0.7752585      TRUE    FALSE                 2           <NA>