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link for the data set used in this video: https://shorturl.at/hsMP3 data set less than 100 for student version: https://shorturl.at/tCW69 In this video, I discuss mediation analysis using SmartPLS 4. I begin by defining mediation and explaining the different types of mediation models, including simple, parallel, and serial mediation. I then discuss the different types of mediation effects, including direct effect only, indirect effect only, both direct and indirect effect, complementary mediation, and competitive mediation. I then walk through an example of mediation analysis using SmartPLS 4. I show how to create the mediation model, calculate the mediation effects, and interpret the results. I also discuss some of the limitations of mediation analysis. The video concludes with a summary of the key points covered in the lecture. Here are some of the key takeaways from the video: Mediation analysis is a statistical method used to determine whether an independent variable affects a dependent variable through a mediator variable. There are three main types of mediation models: simple, parallel, and serial. There are four types of mediation effects: direct effect only, indirect effect only, both direct and indirect effect, complementary mediation, and competitive mediation. Mediation analysis can be performed using SmartPLS 4. Here is a more detailed description of the different types of mediation effects: Direct effect only: This occurs when the independent variable has a direct effect on the dependent variable, but the mediator variable does not have any effect. Indirect effect only: This occurs when the independent variable only has an indirect effect on the dependent variable through the mediator variable. Both direct and indirect effect: This occurs when the independent variable has both a direct and an indirect effect on the dependent variable. Complementary mediation: This occurs when the indirect effect of the mediator variable complements the direct effect of the independent variable. Competitive mediation: This occurs when the indirect effect of the mediator variable competes with the direct effect of the independent variable.