## ----include = FALSE---------------------------------------------------------- knitr::opts_chunk$set( collapse = TRUE, comment = "#>" ) has_data <- nzchar(system.file("extdata", "getMediation_examples.RData", package = "nlpsem")) knitr::opts_chunk$set(eval = has_data) ## ----message = FALSE---------------------------------------------------------- library(nlpsem) mxOption(model = NULL, key = "Default optimizer", "CSOLNP", reset = FALSE) ## ----message = FALSE---------------------------------------------------------- load(system.file("extdata", "getMediation_examples.RData", package = "nlpsem")) ## ----message = FALSE, eval = FALSE-------------------------------------------- # # Load ECLS-K (2011) data # data("RMS_dat") # RMS_dat0 <- RMS_dat # # Re-baseline the data so that the estimated initial status is for the # # starting point of the study # baseT <- RMS_dat0$T1 # RMS_dat0$T1 <- RMS_dat0$T1 - baseT # RMS_dat0$T2 <- RMS_dat0$T2 - baseT # RMS_dat0$T3 <- RMS_dat0$T3 - baseT # RMS_dat0$T4 <- RMS_dat0$T4 - baseT # RMS_dat0$T5 <- RMS_dat0$T5 - baseT # RMS_dat0$T6 <- RMS_dat0$T6 - baseT # RMS_dat0$T7 <- RMS_dat0$T7 - baseT # RMS_dat0$T8 <- RMS_dat0$T8 - baseT # RMS_dat0$T9 <- RMS_dat0$T9 - baseT # RMS_dat0$ex1 <- scale(RMS_dat0$Approach_to_Learning) # xstarts <- mean(baseT) ## ----message = FALSE, eval = FALSE-------------------------------------------- # Med2_LGCM_BLS <- getMediation( # dat = RMS_dat0, t_var = rep("T", 2), y_var = "M", m_var = "R", # x_type = "baseline", x_var = "ex1", curveFun = "bilinear spline", # records = list(1:9, 1:9), tries = 10, # paramOut = TRUE # ) ## ----------------------------------------------------------------------------- Med2_LGCM_BLS@Estimates ## ----message = FALSE, eval = FALSE-------------------------------------------- # set.seed(20191029) # Med3_LGCM_BLS <- getMediation( # dat = RMS_dat0, t_var = rep("T", 3), y_var = "S", m_var = "M", x_type = "longitudinal", # x_var = "R", curveFun = "bilinear spline", records = list(2:9, 1:9, 1:9), # tries = 10, paramOut = TRUE # ) ## ----------------------------------------------------------------------------- Med3_LGCM_BLS@Estimates