A non-technical guide for conducting open and reproducible PLS-SEM analyses using the "cSEM" package in R/RStudio

<br> # Install the fillowing packages and recall libraries in R using this command: if (!require(cSEM, quietly = TRUE)) { install.packages("devtools") library(devtools) install_github("M-E-Rademaker/cSEM") } library(cSEM) # Now Set a working directory using this command: setwd("D:/Secondary") # Specify your model satisfaction_mod # Reflective measurement model IMAG =~ imag1 + imag2 + imag3 SAT =~ sat1 + sat2 + sat3 + sat4 LOY =~ loy1 + loy2 + loy3 + loy4 # Structural model LOY ~ SAT + IMAG " # Estimate model satisfaction_res .model = satisfaction_mod, .PLS_weight_scheme_inner = "path", .disattenuate = FALSE, .tolerance = 1e-07) summarize(satisfaction_res) assess(satisfaction_res) # We note that the output of the summarize() function contains a lot of NAs. This is due to the fact that we did not explicitly require to use the bootstrap to perform inference. To do that, we need to include the .resample_method = "bootstrap" argument as in the next example: satisfaction_boot .model = satisfaction_mod, .PLS_weight_scheme_inner = "path", .disattenuate = TRUE, .tolerance = 1e-07, .resample_method = "bootstrap", .R = 1000, .seed = 1406) summarize(satisfaction_boot, .ci = "CI_percentile")