Regression in SmartPLS 4.0

SmartPLS Click Path Guide

This guide translates the shared paper into practical SmartPLS 4 menu steps.

A. Import the HBAT-Style Dataset

  1. Open SmartPLS 4.
  2. Create a new project.
  3. Import datasets/hbat_smartpls_regression_case.csv.
  4. Confirm that X1 to X23 are visible.
  5. Save the project.

B. Build the Multiple Linear Regression Model

  1. Create a new model.
  2. Add X19 as the dependent variable.
  3. Add X6, X7, X9, X11, and X12 as independent variables.
  4. Draw arrows from each independent variable to X19.
  5. Keep the intercept in the model unless your instructor asks for a no-intercept model.
  6. Save the model as HBAT Linear Regression.

C. Run Multiple Linear Regression

  1. Select Calculate.
  2. Choose Regression.
  3. Use a two-tailed test unless you pre-specified directional hypotheses.
  4. Use a 0.05 significance level.
  5. Start with normal standard errors.
  6. If diagnostics suggest heteroscedasticity or leverage concerns, compare HC3 or HC4 robust standard errors.
  7. Tick Open report.
  8. Start calculation.

D. Export Linear Regression Results

Export:

E. Build the Logistic Regression Model

  1. Create a new model.
  2. Add X4 as the binary dependent variable.
  3. Add X6 to X18 as independent variables.
  4. Draw arrows from all independent variables to X4.
  5. Save the model as HBAT Logistic Regression.

F. Run Logistic Regression

  1. Select Calculate.
  2. Choose Logistic Regression.
  3. Use default maximum iteration and stop criterion settings unless convergence fails.
  4. Use a two-tailed test and 0.05 significance level unless the study design justifies another choice.
  5. Tick Open report.
  6. Start calculation.

G. Export Logistic Regression Results

Export:

H. Reporting Rule

Do not paste SmartPLS output alone. Convert every exported table into: