latents-summary: Summarise latents results

In latents: Multilevel Latent Profile, Class and Transition Models

Summarise latents results

Description

Summary methods for fitted models, enumerations, bootstrap tests, covariate and transition models, mixture regressions and pooled imputations. A summary collects the model's main tables and diagnostics; printing it shows each table to a set depth.

Usage

## S3 method for class 'multilpa_additive'
summary(object, level = 0.95, vcov_type = c("observed", "robust", "opg"), ...)

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

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

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

## S3 method for class 'latents_growth_mixture'
summary(object, level = 0.95, vcov_type = NULL, ...)

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

## S3 method for class 'latents_mixture_regression'
summary(object, level = 0.95, vcov_type = NULL, ...)

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

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

Arguments

object	An object returned by a latents function.
level	Confidence level for the reported intervals, strictly between zero and one.
vcov_type	"observed", "robust" or "opg", as for parameter_inference(). For mixture regressions and growth mixtures, NULL reuses the inference stored with the fit, or, when there is none, uses robust errors for a weighted fit and observed otherwise.
...	Ignored; present for compatibility with summary().

Value

An object of class ⁠summary_<class>⁠ holding the summarised tables. Print it, or read any table with get_results() or as.data.frame().

See Also

latents-print, latents-as-data-frame, get_results().

Examples

fit <- multilpa(course_engagement, c("browse", "lectures", "forum_read"),
                "student", n_profiles = 2, n_group_classes = 2,
                n_starts = 2, seed = 1)
print(summary(fit), rows = 3)

latents documentation built on Oct. 16, 2026, 5:09 p.m.