Dr. Manishika Jain in this lecture explains factor analysis. Introduction to Factor Analysis: Factor Loading, Factor Scoring & Factor Rotation.
NET Psychology postal course -
NET Psychology MCQs -
IAS Psychology -
IAS Psychology test series -
Factor Analysis and PCA
Reduce large number of variables into fewer number of factors
Co-variation is due to latent variable that exert casual influence on observed variables
Communalities – each variable’s variance that can be explained by factors
Types of Factoring
• PCA – maximum variance for 1st factor; removes that and uses maximum for 2nd factor and so on…
• Common Factor Analysis – Same as factor analysis (only common variance – used in CFA)
• Image Factoring – correlation matrix; uses OLS regression matrix
• Maximum Likelihood Method – on correlation matrix
• Alpha Factoring
• Weight Square
Estimate communalities - each variable’s variance that can be explained by factor.
See factors are retained
Factor rotation - Procedure in which the eigenvectors (factors) are rotated in an attempt to achieve simple structure.
Factor loading - Relation of each variable to the underlying factor. Output of a simple factor analysis looking at indicators of wealth, with just six variables and two resulting factors
6 variables: Income, education, occupation, house value, public parks and crimes
2 factors: individual socioeconomic status and neighborhood socioeconomic status
Factor Score – if value of variables are given then factor values can be predicted
Interpretation
NET Psychology postal course -
NET Psychology MCQs -
IAS Psychology -
IAS Psychology test series -
Factor Analysis and PCA
Reduce large number of variables into fewer number of factors
Co-variation is due to latent variable that exert casual influence on observed variables
Communalities – each variable’s variance that can be explained by factors
Types of Factoring
• PCA – maximum variance for 1st factor; removes that and uses maximum for 2nd factor and so on…
• Common Factor Analysis – Same as factor analysis (only common variance – used in CFA)
• Image Factoring – correlation matrix; uses OLS regression matrix
• Maximum Likelihood Method – on correlation matrix
• Alpha Factoring
• Weight Square
Estimate communalities - each variable’s variance that can be explained by factor.
See factors are retained
Factor rotation - Procedure in which the eigenvectors (factors) are rotated in an attempt to achieve simple structure.
Factor loading - Relation of each variable to the underlying factor. Output of a simple factor analysis looking at indicators of wealth, with just six variables and two resulting factors
6 variables: Income, education, occupation, house value, public parks and crimes
2 factors: individual socioeconomic status and neighborhood socioeconomic status
Factor Score – if value of variables are given then factor values can be predicted
Interpretation
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