Convert latents results to a data frame

as.data.frame() returns the primary table of a latents result: the measurement parameters of a fitted model, the candidates of an enumeration, the test of a bootstrap, and so on. It is the same table as get_results(x); get_results() with what = returns the others.

Usage

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

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

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

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

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

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

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

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

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

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

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

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

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

Arguments

x

An object returned by a latents function, or the summary() of one.

row.names

Passed to data.frame(); NULL gives default row names.

optional

Ignored; present for compatibility with as.data.frame().

...

Must be empty. An argument here raises latents_bad_argument naming it, rather than being dropped.

Value

A base data.frame, one row per parameter, candidate or test depending on the object.

See also

get_results(), latents-print, latents-summary.

Examples

fit <- multilpa(course_engagement, c("browse", "lectures", "forum_read"),
                "student", n_profiles = 2, n_group_classes = 2,
                n_starts = 2, seed = 1)
head(as.data.frame(fit))
#>   profile  indicator       mean  variance standard_deviation
#> 1       1     browse  0.5388561 0.5896074          0.7678590
#> 2       1   lectures  0.4194852 0.8397745          0.9163921
#> 3       1 forum_read  0.6130248 0.4870705          0.6979044
#> 4       2     browse -0.7837817 0.5052548          0.7108127
#> 5       2   lectures -0.6102031 0.5489694          0.7409247
#> 6       2 forum_read -0.8914110 0.3495553          0.5912320
#>   mean_standard_error variance_standard_error
#> 1          0.02838311              0.03074947
#> 2          0.03346109              0.04258343
#> 3          0.02749619              0.02753482
#> 4          0.03381727              0.03432265
#> 5          0.03327362              0.03480293
#> 6          0.02779554              0.02342192