KRISHI
ICAR RESEARCH DATA REPOSITORY FOR KNOWLEDGE MANAGEMENT
(An Institutional Publication and Data Inventory Repository)
"Not Available": Please do not remove the default option "Not Available" for the fields where metadata information is not available
"1001-01-01": Date not available or not applicable for filling metadata infromation
"1001-01-01": Date not available or not applicable for filling metadata infromation
Please use this identifier to cite or link to this item:
http://krishi.icar.gov.in/jspui/handle/123456789/73607
Full metadata record
DC Field | Value | Language |
---|---|---|
dc.contributor.author | Deepak Singh | en_US |
dc.contributor.author | Pradip Basak | en_US |
dc.contributor.author | Raju Kumar | en_US |
dc.date.accessioned | 2022-07-16T05:22:45Z | - |
dc.date.available | 2022-07-16T05:22:45Z | - |
dc.date.issued | 2020-12-21 | - |
dc.identifier.citation | Singh, D., Basak, P. and Kumar, R. (2020). Construction of Composite Index under Complex Surveys. Project report, ICAR-IASRI, New Delhi, India | en_US |
dc.identifier.issn | Not Available | - |
dc.identifier.uri | http://krishi.icar.gov.in/jspui/handle/123456789/73607 | - |
dc.description | Not Available | en_US |
dc.description.abstract | Principal component (PC) based index accounts for the effect of multicollinearity among the indicator variables through the eigen values and eigen vectors derived from the variance-covariance matrix using maximum likelihood (ML)/ordinary least squares (OLS) methods of estimation. However, these methods of estimation of variance covariance matrix are based on the assumption that sample elements, on which the indicator variables are measured, are independent and identically distributed. In complex survey designs, the independence assumption of units does not hold that leads to erroneous estimation of variance covariance matrix under OLS methods. Therefore, in case of survey data there is a need to develop PC based index using survey weights and auxiliary information which excludes the effect of multicollinearity among the indicator variables as well as accounts for the effect of complex survey designs through which the sample data is collected. Therefore under this study different methods of indices development are proposed which are capable to incorporate the survey weights and auxiliary information available in the data. | en_US |
dc.description.sponsorship | Not Available | en_US |
dc.language.iso | English | en_US |
dc.publisher | ICAR-IASRI | en_US |
dc.subject | Multicollinearity | en_US |
dc.subject | Survey weight | en_US |
dc.subject | Food consumption index | en_US |
dc.subject | Household consumer expenditure surveys | en_US |
dc.subject | Principal component | en_US |
dc.subject | Index | en_US |
dc.title | Construction of Composite Index under Complex Surveys | en_US |
dc.title.alternative | PROJECT REPORT | en_US |
dc.type | Project Report | en_US |
dc.publication.projectcode | AGEDIASRISIL201801800127 | en_US |
dc.publication.volumeno | Not Available | en_US |
dc.publication.pagenumber | 1-62 | en_US |
dc.publication.divisionUnit | Division of Sample Surveys | en_US |
dc.publication.sourceUrl | Not Available | en_US |
dc.publication.authorAffiliation | ICAR::Indian Agricultural Statistics Research Institute | en_US |
dc.ICARdataUseLicence | http://krishi.icar.gov.in/PDF/ICAR_Data_Use_Licence.pdf | en_US |
Appears in Collections: | AEdu-IASRI-Publication |
Files in This Item:
File | Description | Size | Format | |
---|---|---|---|---|
Project report - INDEX.pdf | 2.14 MB | Adobe PDF | View/Open |
Items in KRISHI are protected by copyright, with all rights reserved, unless otherwise indicated.