Description: In lecture 47 ARM, We will cover following topics:

How to calculate convergent and discriminant validity in SPSS and Excel? - - - Validity and its types
How to calculate convergent validity in SPSS and Excel?
How to calculate discriminant validity in SPSS and Excel?
How to calculate Average Variance Extracted in SPSS and Excel?
How to calculate Fornell-Lorcker Test in SPSS?
What is Validity ? (درستگی)
How many types of Validity?
What is Convergent Validity? (ہم آہنگی)
What is Face validity?
What is Content Validity?
What is Criterion Validity?
What is Predictive Validity?
What is Concurrent Validity?
Convergent Validity(ہم آہنگی)
Discriminant Validity(امتیاز)
First, let's talk about convergent validity. This type of validity is used to determine whether or not a measure is an accurate measure of a certain construct. To calculate this in SPSS, you'll need to use the Factor Analysis procedure. You will enter the correlation matrix of your variables, then the computer will generate a factor matrix and indicator scores. These scores represent the convergent validity of your measure. For calculating convergent validity in Excel, you'll need to calculate the correlation matrix of your variables. This matrix will show the relationship between the variables and how much they are related. You'll need to look for strong correlations between variables that measure similar traits. If the variables are highly correlated, then the convergent validity is high. Now let's talk about discriminant validity. This type of validity is used to determine whether or not the measure is distinct from other constructs. To calculate this in SPSS, you'll need to use the Multivariate Analysis of Variance procedure. You will enter the correlation matrix of your variables, then the computer will generate a new matrix of scores. These scores represent the discriminant validity of your measure. For calculating discriminant validity in Excel, you'll need to look for low correlations between variables that measure different traits. If the variables are not correlated, then the discriminant validity is high.
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