## ----setup, include = FALSE--------------------------------------------------- knitr::opts_chunk$set( collapse = TRUE, comment = "#>", message = FALSE, warning = FALSE, fig.width = 6 ) ## ----load pupil data, echo = TRUE--------------------------------------------- library(SCoRES) library(mgcv) data(pupil) ## ----fit gam-fpca model-1, echo = TRUE---------------------------------------- pupil_fpca <- SCoRES::prepare_pupil_fpca(pupil) fosr_mod <- mgcv::bam(percent_change ~ s(seconds, k=30, bs="cr") + s(seconds, by = use, k=30, bs = "cr") + s(id, by = Phi1, bs="re") + s(id, by = Phi2, bs="re") + s(id, by = Phi3, bs="re") + s(id, by = Phi4, bs="re"), method = "fREML", data = pupil_fpca, discrete = TRUE) ## ----pupil_plot_cs_cma, echo = TRUE, eval = FALSE----------------------------- # # CMA approach # results_pupil_cma <- SCoRES::SCB_functional_outcome( # data_df = pupil, # object = fosr_mod, # method = "cma", # fitted = TRUE, # alpha = 0.05, # outcome = "percent_change", # domain = "seconds", # subset = c("use = 1"), # id = "id") # # results_pupil_cma <- tibble::as_tibble(results_pupil_cma) # plot_cs(results_pupil_cma, # levels = c(-18, -20, -22, -24), # x = results_pupil_cma$domain, # mu_hat = results_pupil_cma$mu_hat, # xlab = "Seconds", # ylab = "Percent_Outcome", # level_label = T, # min.size = 40, # palette = "Spectral", # color_level_label = "black") ## ----ccds_plot_cs_pupil_para, echo = TRUE, eval = FALSE----------------------- # #CMA approach for parameter function # results_pupil_cma_para <- SCoRES::SCB_functional_outcome( # data_df = pupil, # object = fosr_mod, # method = "cma", # fitted = FALSE, # alpha = 0.05, # outcome = "percent_change", # domain = "seconds", # subset = c("use = 1"), # id = "id") # # results_pupil_cma_para <- tibble::as_tibble(results_pupil_cma_para) # plot_cs(results_pupil_cma_para, # levels = c(4.5, 5, 5.5, 6), # x = results_pupil_cma_para$domain, # mu_hat = results_pupil_cma_para$mu_hat, # xlab = "Seconds", # ylab = "Percent_Outcome", # level_label = T, # min.size = 40, # palette = "Spectral", # color_level_label = "black") ## ----pupil_plot_cs_multiplier, echo = TRUE------------------------------------ # Multiplier-t Bootstrap results_pupil_multiplier <- SCoRES::SCB_functional_outcome( data_df = pupil, object = fosr_mod, method = "multiplier", fitted = TRUE, alpha = 0.05, outcome = "percent_change", domain = "seconds", subset = c("use = 1"), id = "id") results_pupil_multiplier <- tibble::as_tibble(results_pupil_multiplier) plot_cs(results_pupil_multiplier, levels = c(-18, -20, -22, -24), x = results_pupil_multiplier$domain, mu_hat = results_pupil_multiplier$mu_hat, xlab = "Seconds", ylab = "Percent_Outcome", level_label = T, min.size = 40, palette = "Spectral", color_level_label = "black") ## ----pupil_plot_cs_multiplier_para, echo = TRUE------------------------------- results_pupil_multiplier_para <- SCoRES::SCB_functional_outcome( data_df = pupil, object = fosr_mod, method = "multiplier", fitted = FALSE, alpha = 0.05, outcome = "percent_change", domain = "seconds", subset = c("use = 1"), id = "id") results_pupil_multiplier_para <- tibble::as_tibble(results_pupil_multiplier_para) plot_cs(results_pupil_multiplier_para, levels = c(4.5, 5, 5.5, 6), x = results_pupil_multiplier_para$domain, mu_hat = results_pupil_multiplier_para$mu_hat, xlab = "Seconds", ylab = "Percent_Outcome", level_label = T, min.size = 40, palette = "Spectral", color_level_label = "black") ## ----pupil_plot_cs_multiplier_overall, echo = TRUE, eval = FALSE-------------- # results_pupil_multiplier_overall <- SCoRES::SCB_functional_outcome( # data_df = pupil, # method = "multiplier", # fitted = TRUE, # alpha = 0.05, # outcome = "percent_change", # domain = "seconds", # subset = c("use = 1"), # id = "id") # # results_pupil_multiplier_overall <- tibble::as_tibble(results_pupil_multiplier_overall) # plot_cs(results_pupil_multiplier_overall, # levels = c(-18, -20, -22, -24), # x = results_pupil_multiplier_overall$domain, # mu_hat = results_pupil_multiplier_overall$mu_hat, # xlab = "Seconds", # ylab = "Percent_Outcome", # level_label = T, # min.size = 40, # palette = "Spectral", # color_level_label = "black") ## ----fit gam-fpca model-2, echo = TRUE---------------------------------------- pupil_fpca <- SCoRES::prepare_pupil_fpca(pupil, example = "extended") fosr_mod <- mgcv::bam(percent_change ~ s(seconds, k=30, bs="cr") + s(seconds, by = use, k=30, bs = "cr") + s(seconds, by = age, k = 30, bs = "cr") + s(seconds, by = gender, k = 30, bs = "cr") + s(id, by = Phi1, bs="re") + s(id, by = Phi2, bs="re") + s(id, by = Phi3, bs="re") + s(id, by = Phi4, bs="re"), method = "fREML", data = pupil_fpca, discrete = TRUE) ## ----pupil_plot_cs_cma_2, echo = TRUE, eval = FALSE--------------------------- # # CMA approach # results_pupil_cma <- SCoRES::SCB_functional_outcome( # data_df = pupil, # object = fosr_mod, # method = "cma", # fitted = TRUE, # alpha = 0.05, # outcome = "percent_change", # domain = "seconds", # subset = c("use = 1", # "age = 40", # "gender = 0"), # id = "id") # # results_pupil_cma <- tibble::as_tibble(results_pupil_cma) # plot_cs(results_pupil_cma, # levels = c(-18, -20, -22, -24), # x = results_pupil_cma$domain, # mu_hat = results_pupil_cma$mu_hat, # xlab = "Seconds", # ylab = "Percent_Outcome", # level_label = T, # min.size = 40, # palette = "Spectral", # color_level_label = "black") ## ----pupil_plot_cs_multiplier_2, echo = TRUE---------------------------------- # Multiplier-t Bootstrap results_pupil_multiplier <- SCoRES::SCB_functional_outcome( data_df = pupil, object = fosr_mod, fitted = TRUE, method = "multiplier", alpha = 0.05, outcome = "percent_change", domain = "seconds", subset = c("use = 1", "age = 40", "gender = 0"), id = "id") results_pupil_multiplier <- tibble::as_tibble(results_pupil_multiplier) plot_cs(results_pupil_multiplier, levels = c(-18, -20, -22, -24), x = results_pupil_multiplier$domain, mu_hat = results_pupil_multiplier$mu_hat, xlab = "Seconds", ylab = "Percent_Outcome", level_label = T, min.size = 40, palette = "Spectral", color_level_label = "black")