| as.data.frame.multilpa | R Documentation |
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.
## 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, ...)
x |
An object returned by a latents function, or the |
row.names |
Passed to |
optional |
Ignored; present for compatibility with |
... |
Must be empty. An argument here raises |
A base data.frame, one row per parameter, candidate or test
depending on the object.
get_results(), latents-print, latents-summary.
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))
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