<?xml version="1.0" encoding="UTF-8"?><marc:collection xmlns:marc="http://www.loc.gov/MARC21/slim">
  <marc:record>
    <marc:leader>00000nam  2200000za 4500</marc:leader>
    <marc:controlfield tag="001">9.837379</marc:controlfield>
    <marc:controlfield tag="003">CaOODSP</marc:controlfield>
    <marc:controlfield tag="005">20221107151126</marc:controlfield>
    <marc:controlfield tag="007">cr |||||||||||</marc:controlfield>
    <marc:controlfield tag="008">170529s1993    onc    |o    f|0| 0 eng d</marc:controlfield>
    <marc:datafield tag="040" ind1=" " ind2=" ">
      <marc:subfield code="a">CaOODSP</marc:subfield>
      <marc:subfield code="b">eng</marc:subfield>
    </marc:datafield>
    <marc:datafield tag="041" ind1=" " ind2=" ">
      <marc:subfield code="a">eng</marc:subfield>
      <marc:subfield code="b">fre</marc:subfield>
    </marc:datafield>
    <marc:datafield tag="043" ind1=" " ind2=" ">
      <marc:subfield code="a">n-cn---</marc:subfield>
    </marc:datafield>
    <marc:datafield tag="086" ind1="1" ind2=" ">
      <marc:subfield code="a">CS11-613/93-10E-PDF</marc:subfield>
    </marc:datafield>
    <marc:datafield tag="100" ind1="1" ind2=" ">
      <marc:subfield code="a">Kovacevic, Milorad S.</marc:subfield>
    </marc:datafield>
    <marc:datafield tag="245" ind1="1" ind2="0">
      <marc:subfield code="a">Variance estimation in longitudinal microsimulation </marc:subfield>
      <marc:subfield code="h">[electronic resource] / </marc:subfield>
      <marc:subfield code="c">Milorad S. Kovacevic and Gurupdesh S. Pandher.</marc:subfield>
    </marc:datafield>
    <marc:datafield tag="260" ind1=" " ind2=" ">
      <marc:subfield code="a">[Ottawa] : </marc:subfield>
      <marc:subfield code="b">Statistics Canada, </marc:subfield>
      <marc:subfield code="c">1993.</marc:subfield>
    </marc:datafield>
    <marc:datafield tag="300" ind1=" " ind2=" ">
      <marc:subfield code="a">28 p. : </marc:subfield>
      <marc:subfield code="b">figures.</marc:subfield>
    </marc:datafield>
    <marc:datafield tag="490" ind1="1" ind2=" ">
      <marc:subfield code="a">Working paper ; </marc:subfield>
      <marc:subfield code="v">93-10</marc:subfield>
    </marc:datafield>
    <marc:datafield tag="500" ind1=" " ind2=" ">
      <marc:subfield code="a">Digitized edition from print [produced by Statistics Canada].</marc:subfield>
    </marc:datafield>
    <marc:datafield tag="500" ind1=" " ind2=" ">
      <marc:subfield code="a">"SSMD-93-010 E."</marc:subfield>
    </marc:datafield>
    <marc:datafield tag="500" ind1=" " ind2=" ">
      <marc:subfield code="a">"August 1993."</marc:subfield>
    </marc:datafield>
    <marc:datafield tag="504" ind1=" " ind2=" ">
      <marc:subfield code="a">Includes bibliographic references.</marc:subfield>
    </marc:datafield>
    <marc:datafield tag="520" ind1="3" ind2=" ">
      <marc:subfield code="a">"As a policy development tool, longitudinal microsimulation (MS) modelling is widely used in researching the impact of various policy scenarios on certain characteristics of interest in a hypothetical but representative population. In this context, microsimulation output has analytical and inferential uses rather than merely providing data to construct simple point estimates for descriptive purposes. In general, MS output is autocorrelated so that the direct application of simple variance estimation techniques is inappropriate. The present work addresses the question of how the correlated nature of observations 'collected' during long-run simulation can be overcome. The emphasis is on the design of the MS experiment and the proper choice of the variance estimator. Two designs are considered, the independent runs and the batched run design, and three variance estimators are compared regarding their statistical properties. These ideas are applied to sequences of data produced by the Canadian Population Health Model (POHEM)"--Abstract.</marc:subfield>
    </marc:datafield>
    <marc:datafield tag="546" ind1=" " ind2=" ">
      <marc:subfield code="a">Prefatory material in English and French.</marc:subfield>
    </marc:datafield>
    <marc:datafield tag="692" ind1="0" ind2="7">
      <marc:subfield code="2">gccst</marc:subfield>
      <marc:subfield code="a">Surveys</marc:subfield>
    </marc:datafield>
    <marc:datafield tag="692" ind1="0" ind2="7">
      <marc:subfield code="2">gccst</marc:subfield>
      <marc:subfield code="a">Methodology</marc:subfield>
    </marc:datafield>
    <marc:datafield tag="700" ind1="1" ind2=" ">
      <marc:subfield code="a">Pandher, Gurupdesh S.</marc:subfield>
    </marc:datafield>
    <marc:datafield tag="710" ind1="1" ind2=" ">
      <marc:subfield code="a">Canada. </marc:subfield>
      <marc:subfield code="b">Statistics Canada.</marc:subfield>
      <marc:subfield code="b">Social Survey Methods Division.</marc:subfield>
    </marc:datafield>
    <marc:datafield tag="830" ind1="#" ind2="0">
      <marc:subfield code="a">Working paper (Statistics Canada. Methodology Branch)</marc:subfield>
      <marc:subfield code="v">93-10</marc:subfield>
      <marc:subfield code="w">(CaOODSP)9.834763</marc:subfield>
    </marc:datafield>
    <marc:datafield tag="856" ind1="4" ind2="0">
      <marc:subfield code="q">PDF</marc:subfield>
      <marc:subfield code="s">4.13 MB</marc:subfield>
      <marc:subfield code="u">https://publications.gc.ca/collections/collection_2017/statcan/11-613/CS11-613-93-10-eng.pdf</marc:subfield>
    </marc:datafield>
    <marc:datafield tag="986" ind1=" " ind2=" ">
      <marc:subfield code="a">11-613</marc:subfield>
    </marc:datafield>
  </marc:record>
</marc:collection>
