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| 01978nam 2200349za 4500 |
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| 001 | 9.839040 |
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| 003 | CaOODSP |
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| 005 | 20221107151523 |
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| 007 | cr ||||||||||| |
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| 008 | 170628s2000 onc |o f|0| 0 eng d |
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| 040 | |aCaOODSP|beng |
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| 041 | |aeng|bfre |
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| 043 | |an-cn--- |
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| 086 | 1 |aCS11-613/2000-4E-PDF |
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| 100 | 1 |aKovacevic, Milorad S. |
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| 245 | 12|aA pseudo maximum likelihood approach to inference about hierarchically structured data |h[electronic resource] / |cMilorad S. Kovacevic and Shesh N. Rai. |
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| 260 | |a[Ottawa] : |bStatistics Canada, |c2000. |
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| 300 | |a28 p. : |bfigures. |
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| 490 | 1 |aWorking paper ; |v2000-4 |
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| 500 | |aDigitized edition from print [produced by Statistics Canada]. |
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| 500 | |a"SSMD-2000-004E." |
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| 500 | |a"April 2000." |
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| 504 | |aIncludes bibliographic references. |
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| 520 | |a"An application of the pseudo maximum likelihood method is demonstrated on estimation for a mixed linear model fitted to the dependent observations coming from a hierarchical population. This approach provides a closed form solution for estimating the parameters of the mixed linear models which seems to be simpler than the iterative procedures such as iterative probability weighted least squares method of Pfeffermann et al. (1998) . We also discuss some issues relating to model and sample design hierarchies and their impact on estimation. A small simulation study showed that the proposed procedure is efficient even for small sample sizes at higher levels"--Summary. |
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| 546 | |aSummary in French. |
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| 692 | 07|2gccst|aMethodology |
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| 692 | 07|2gccst|aStatistical analysis |
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| 700 | 1 |aRai, Shesh Nath,|d1960- |
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| 710 | 1 |aCanada. |bStatistics Canada. |bMethodology Branch. |
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| 830 | #0|aWorking paper (Statistics Canada. Methodology Branch)|v2000-4|w(CaOODSP)9.834763 |
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| 856 | 40|qPDF|s2.50 MB|uhttps://publications.gc.ca/collections/collection_2017/statcan/11-613/CS11-613-2000-4-eng.pdf |
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