Predict cluster assignment and outcome based on LUCID model

Predict cluster assignment and outcome based on LUCID model

Usage

predict_lucid(model, G, Z, Y = NULL, CoG = NULL, CoY = NULL, response = TRUE)

Arguments

model

A model fitted and returned by est_lucid

G

Exposures, a numeric vector, matrix, or data frame. Categorical variable should be transformed into dummy variables. If a matrix or data frame, rows represent observations and columns correspond to variables.

Z

Omics data, a numeric matrix or data frame. Rows correspond to observations and columns correspond to variables.

Y

Outcome, a numeric vector. Categorical variable is not allowed. Binary outcome should be coded as 0 and 1.

CoG

Optional, covariates to be adjusted for estimating the latent cluster. A numeric vector, matrix or data frame. Categorical variable should be transformed into dummy variables.

CoY

Optional, covariates to be adjusted for estimating the association between latent cluster and the outcome. A numeric vector, matrix or data frame. Categorical variable should be transformed into dummy variables.

response

If TRUE, when predicting binary outcome, the response will be returned. If FALSE, the linear predictor is returned.

Value

A list contains predicted latent cluster and outcome for each observation

Examples

if (FALSE) {
# prepare data
G <- sim_data$G
Z <- sim_data$Z
Y_normal <- sim_data$Y_normal

# fit lucid model
fit1 <- est_lucid(G = G, Z = Z, Y = Y_normal, K = 2, family = "normal")

# prediction on training set
pred1 <- predict_lucid(model = fit1, G = G, Z = Z, Y = Y_normal)
pred2 <- predict_lucid(model = fit1, G = G, Z = Z)
}