Recovering a Basic Space from Issue Scales in R
dc.citation.issueNumber | 7 | en_US |
dc.citation.journalTitle | Journal of Statistical Software | en_US |
dc.citation.volumeNumber | 69 | en_US |
dc.contributor.author | Poole, Keith T. | en_US |
dc.contributor.author | Lewis, Jeffrey B. | en_US |
dc.contributor.author | Rosenthal, Howard | en_US |
dc.contributor.author | Lo, James | en_US |
dc.contributor.author | Carroll, Royce | en_US |
dc.date.accessioned | 2017-05-02T21:09:55Z | en_US |
dc.date.available | 2017-05-02T21:09:55Z | en_US |
dc.date.issued | 2016 | en_US |
dc.description.abstract | basicspace is an R package that conducts Aldrich-McKelvey and Blackbox scaling to recover estimates of the underlying latent dimensions of issue scale data. We illustrate several applications of the package to survey data commonly used in the social sciences. Monte Carlo tests demonstrate that the procedure can recover latent dimensions and reproduce the matrix of responses at moderate levels of error and missing data. | en_US |
dc.identifier.citation | Poole, Keith T., Lewis, Jeffrey B., Rosenthal, Howard, et al.. "Recovering a Basic Space from Issue Scales in R." <i>Journal of Statistical Software,</i> 69, no. 7 (2016) Foundation for Open Access Statistics: https://doi.org/10.18637/jss.v069.i07. | en_US |
dc.identifier.doi | https://doi.org/10.18637/jss.v069.i07 | en_US |
dc.identifier.uri | https://hdl.handle.net/1911/94113 | en_US |
dc.language.iso | eng | en_US |
dc.publisher | Foundation for Open Access Statistics | en_US |
dc.rights | This work is licensed under the Creative Commons Attribution 3.0 Unported License | en_US |
dc.rights.uri | https://creativecommons.org/licenses/by/3.0/us/ | en_US |
dc.subject.keyword | multivariate | en_US |
dc.subject.keyword | R | en_US |
dc.subject.keyword | scaling | en_US |
dc.title | Recovering a Basic Space from Issue Scales in R | en_US |
dc.type | Journal article | en_US |
dc.type.dcmi | Text | en_US |
dc.type.publication | publisher version | en_US |
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