{"id":2953,"date":"2021-08-24T06:11:27","date_gmt":"2021-08-24T06:11:27","guid":{"rendered":"https:\/\/researchwithfawad.com\/?page_id=2953"},"modified":"2021-09-11T04:52:23","modified_gmt":"2021-09-11T04:52:23","slug":"how-to-start-data-analysis-using-smart-pls","status":"publish","type":"page","link":"https:\/\/researchwithfawad.com\/index.php\/lp-courses\/basic-and-advance-data-analysis-using-smart-pls\/how-to-start-data-analysis-using-smart-pls\/","title":{"rendered":"How to Start Data Analysis using SMART-PLS"},"content":{"rendered":"\t\t
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Introduction to Data Analysis using SMART-PLS<\/h1>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t
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Learn to use SMART-PLS from scratch, the tutorials are helpful even if you haven’t heard of SMART-PLS before. <\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t

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Understand the Basics of Data Analysis with SMART-PLS<\/h4>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t
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SmartPLS is a software with graphical user interface for variance-based structural equation modeling using the partial least squares path modeling method. Increasingly a number of scholar(s) and academics are using SMART-PLS for data analysis in their research studies.<\/p>

In SEM, a model is tested for quality of the measures (Measurement Model) and next for the\u00a0 interrelationship between the variables (Structural Model). The session discusses in detail the Measurement and Structural model.<\/p>

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Measurement Model <\/h3>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t
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Measurement Model includes assessment of Quality of the Constructs including<\/p>

Reliability<\/h4>

Reliability is the assessment of the internal consistency of the constructs. A measure is said to have a high reliability if it produces similar results under same conditions. Reliability in SMART-PLS is assessed using Cronbach’s Alpha and Composite Reliability.<\/p>

Construct Validity<\/h4>
Validity is the assessment of whether a scale measures the concept what it is intended to measure. Construct validity is assessed through establishing Convergent and Discriminant Validity.<\/div>

Convergent Validity:<\/strong> Convergent validity is established when items in a particular measure converge to represent the underlying construct. Statistically convergent validity is established when Average Variance Extracted (AVE) is >0.50.<\/p>

Discriminant Validity:<\/strong> Discriminant validity is established to ascertain the distinctiveness of the constructs in the study. It shows that constructs in the study have their own individual identity and are not too highly co-related with other constructs in the study.Discriminant validity in SMART-PLS is established using three different techniques.<\/p>

  1. Fornell and Larcker Criterion<\/li>
  2. Cross Loadings<\/li>
  3. Heterotrait-Monotrait (HTMT) Ratio<\/li><\/ol>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t
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    Structural Model <\/h3>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t
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    Structural Model focuses on assessing the inter-relationship between the variables. The inter-relationship may only have an IV and DV (Direct Relationship), mediation analysis with a mediator in the linkage between two variables, or moderation analysis with a third variable strengthening or weakening the existing relationship between two variables.<\/p>

    The video tutorials discuss the basics of how to design and run a model in SMART-PLS. The videos further elaborate on the results and their interpretation.<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t

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    Other SmartPLS Tutorials<\/h5>