SCoRES (version 0.1.2)

prepare_pupil_fpca: Prepare Pupil FPCA Dataset

Description

Processes data by fitting a mean GAM model, extracting residuals, performing FPCA, and merging the results to create an enhanced dataset for functional regression analysis.

Usage

prepare_pupil_fpca(input_data, k_mean = 30, k_fpca = 15, example = "original")

Value

A tibble containing:

• Original pupil variables

• FPCA eigenfunctions (Phi1, Phi2,...)

• Sorted by ID and domain

Arguments

input_data

Raw pupil data

k_mean

Number of basis functions for mean model smooth terms (default: 30)

k_fpca

Number of knots for FPCA estimation (default: 15)

example

Choice for different model. If example = "original", will only include use as the only covariate. If example = "original", will include use, age and gender as covariates.

Examples

if (requireNamespace("mgcv", quietly = TRUE)) {
data(pupil)
processed_data <- prepare_pupil_fpca(pupil)

processed_data <- prepare_pupil_fpca(pupil, k_mean = 5, k_fpca = 5)
}