The use of discrete data in principal component analysis for socio-economic status evaluation

Kolenikov, Stanislav; & Angeles, Gustavo. (2005). The use of discrete data in principal component analysis for socio-economic status evaluation. UNC Chapel Hill.

Citation:

Kolenikov, Stanislav; & Angeles, Gustavo. (2005). The use of discrete data in principal component analysis for socio-economic status evaluation. UNC Chapel Hill.

Citation Export File (RIS Format):
Octet Stream icon

1381.ris — Octet Stream, 958 bytes

Abstract:

Outline
1. Motivation for socio-economic status (slide 3)
Who is interested in SES, and why?
2. Principal component analysis (slide 11)
Is this a reasonable procedure to generate weights for SES index?
3. Applications: Bangladesh DHS+, 2000 (slide 23) and Russia, RLMS 1994–2001 (slide 34)
Does it work for developing countries? Does it work for middle income countries?
Does it work with binary data only?
4. Monte Carlo study of the different flavors of PCA (slide 40)
Can we make any general conclusions about the methods?
5. Conclusions and references (slide 48)
How much room is there for improvement?

URL:

http://www.unc.edu/~skolenik/talks/Gustavo-Stas-PCA-generic.pdf

Keyword(s):

Notes:

Reference Type:
GEN

Secondary Title:

Series Title:

Author(s):
Kolenikov, Stanislav
Angeles, Gustavo

Editor(s):

Series Author(s):

Year Published:
2005

Date Published:

Journal Name:

Volume Number:

Issue Number:

Start Page Number:

End Page Number:

Edition:

Series Volume:

Publisher:
UNC Chapel Hill

City of Publication:

ISSN/ISBN:

DOI:

PMCID:

NIHMSID:

Reference ID:
1381

Miscellaneous:

Personal tools

The use of discrete data in principal component analysis for socio-economic status evaluation