SMART PLS 4 Lecture 3: Assesing Reflective Measurement Model; Reliability, loading, validity. скачать в хорошем качестве

SMART PLS 4 Lecture 3: Assesing Reflective Measurement Model; Reliability, loading, validity.

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 This lecture is part of a series on structural equation modeling (SEM) using SmartPLS 4. In this lecture, we will discuss the following topics related to reflective measurement models: Reliability: How to assess the reliability of reflective measurement models. Loadings: How to interpret the loadings of reflective indicators. Validity: How to assess the validity of reflective measurement models. We will also use a real-world data set to illustrate these concepts. The target audience for this lecture is researchers who are new to SEM using SmartPLS 4. This lecture will provide a basic understanding of the concepts of reliability, loadings, and validity, and how to assess them in SmartPLS 4. Here are some of the key takeaways from this lecture: Reliability is a measure of how consistent the measurements are. Loadings are the correlations between the indicators and the constructs they measure. Validity is a measure of how well the constructs measure the theoretical constructs they are supposed to measure. I hope this summary is helpful! Let me know if you have any other questions. Here are some additional details about the topics discussed in the lecture: Reliability: Reliability is a measure of how consistent the measurements are. There are a variety of methods that can be used to assess reliability, including Cronbach's alpha and composite reliability. Loadings: Loadings are the correlations between the indicators and the constructs they measure. Loadings should be high, typically above 0.70. Validity: Validity is a measure of how well the constructs measure the theoretical constructs they are supposed to measure. There are a variety of methods that can be used to assess validity, including convergent validity and discriminant validity.