summary_lucid: Summarize results of the early LUCID model

In LUCIDus: LUCID with Multiple Omics Data

Summarize results of the early LUCID model

Description

Assembles the reported quantities for a fitted LUCID model and, by default, prints them. The same components are returned invisibly as a list of class sumlucid_early, so they can be extracted programmatically rather than parsed from the printed output.

Two conventions are worth noting when reading the output. Outcome effects are printed as an intercept – cluster 1's level – followed by explicit contrasts of each remaining cluster against it, so the second row is a between-cluster difference and not that cluster's own mean. And the parameter tables are restricted to the features the model retained, so their dimensions match the fit rather than the original input.

Usage

summary_lucid(object, ...)

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

Arguments

object	A LUCID model fitted by estimate_lucid or lucid.
...	Additional arguments. boot.se accepts an object returned by boot_lucid, whose confidence limits are then shown alongside the point estimates. auto_print = FALSE suppresses printing and returns the summary list only.

Value

A list of class sumlucid_early with components:

BIC, loglik

The Bayesian information criterion and the observed-data log-likelihood at the estimates. Also repeated inside model_fit, alongside n_parameters, the effective parameter count the BIC charges (Eq 13, reduced per Eq 18 when a penalty deselected variables).

model_info

The outcome family, the number of clusters K, n_observations, and n_features, which counts retained exposures and omics features.

feature_selection

Which exposures and omics features survived, and how many were dropped.

regularization

The penalties in force, Rho_G, Rho_Z_Mu and Rho_Z_Cov.

parameters

Estimates restricted to the retained features: beta (exposure-to-cluster, intercept column always kept along with any covariate columns), mu (cluster-specific omics means) and gamma (cluster-to-outcome, in both absolute and reference-coded form).

missing_data

The fit's missing_summary; see estimate_lucid.

boot.se

The boot.se argument as supplied, or NULL.

When boot.se is supplied, every printed bootstrap CI table (G-to-X, cluster-to-Y, and cluster-specific omics means) gains a sig column: "*" where the normal-theory confidence interval excludes 0, "" otherwise.

See Also

boot_lucid for the confidence limits, and predict_lucid for cluster and outcome prediction.

Examples

# use simulated data (a small subset keeps the example quick)
G <- sim_data$G[1:150, , drop = FALSE]
Z <- sim_data$Z[1:150, , drop = FALSE]
Y_normal <- sim_data$Y_normal[1:150]

# fit lucid model
fit1 <- estimate_lucid(G = G, Z = Z, Y = Y_normal, lucid_model = "early", family = "normal", K = 2,
seed = 1008, max_itr = 20, max_tot.itr = 50)

# conduct bootstrap resampling
boot1 <- suppressWarnings(
  boot_lucid(G = G, Z = Z, Y = Y_normal, lucid_model = "early", model = fit1, R = 3)
)

# summarize lucid model
summary(fit1)

# summarize lucid model with bootstrap CIs
summary(fit1, boot.se = boot1)

LUCIDus documentation built on Sept. 3, 2026, 1:06 a.m.