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PCA for Socio-Economic Status Analysis by Mohammad Nahid Mia is a document available to read on EtoBox.

What is PCA for Socio-Economic Status Analysis about?

The document discusses using principal component analysis (PCA) to generate weights for constructing a socioeconomic status (SES) index from discrete data. PCA works by finding linear combinations of variables that explain the most variability in the data. It is commonly used but was developed for continuous data. The document evaluates several approaches to applying PCA to discrete data, including ignoring discreteness (ordinal PCA), using dummy variables (Filmer-Pritchett procedure), and estimating polych

Author

Mohammad Nahid Mia

Language

EN