<?xml version="1.0" encoding="UTF-8"?>
<record
    xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance"
    xsi:schemaLocation="http://www.loc.gov/MARC21/slim http://www.loc.gov/standards/marcxml/schema/MARC21slim.xsd"
    xmlns="http://www.loc.gov/MARC21/slim">

  <leader>01857pab a2200181 454500</leader>
  <controlfield tag="008">180718b2015   xxu||||| |||| 00| 0 eng d</controlfield>
  <datafield tag="100" ind1=" " ind2=" ">
    <subfield code="a">Zhu, Ling </subfield>
  </datafield>
  <datafield tag="245" ind1=" " ind2=" ">
    <subfield code="a">A Bayesian approach to measurement bias in networking studies</subfield>
  </datafield>
  <datafield tag="260" ind1=" " ind2=" ">
    <subfield code="c">2015</subfield>
  </datafield>
  <datafield tag="300" ind1=" " ind2=" ">
    <subfield code="a">p.542-564.</subfield>
  </datafield>
  <datafield tag="362" ind1=" " ind2=" ">
    <subfield code="a">Sep</subfield>
  </datafield>
  <datafield tag="520" ind1=" " ind2=" ">
    <subfield code="a">The study of managerial networking has been growing in the field of public administration; a field that analyzes how managers in open system organizations interact with different external actors and organizations. Coincident with this interest in managerial networking is the use of self-reported survey data to measure managerial behavior in building and maintaining networks. One predominant approach is to generate factor indices of networking activity from ordinal scales. However, when public managers answer survey questions with ordinal scales to describe their networking activities, the answers may be subject to various response biases. Consequently, the use of factor indices may lead to biased measurements that misrepresent managerial networking. As an alternative, we build on studies that apply the item response theory (IRT) as a measurement strategy and propose a Bayesian alternative. To tap managers' latent effort put in networking activity, the Bayesian Generalized Partial Credit Model allows us to select a one-dimensional networking scale from multiple ordinal survey items. Using 12 such items in a mail survey of nearly 1,000 American hospital managers, we demonstrate the advantage of using the Bayesian IRT model over factor-analytic models in a substantive test of how managerial networking affects organizational performance. - Reproduced.</subfield>
  </datafield>
  <datafield tag="650" ind1=" " ind2=" ">
    <subfield code="a">Public administration</subfield>
  </datafield>
  <datafield tag="700" ind1=" " ind2=" ">
    <subfield code="a">Torenvlied, Rene </subfield>
  </datafield>
  <datafield tag="700" ind1=" " ind2=" ">
    <subfield code="a">Robinson,  Scott E. </subfield>
  </datafield>
  <datafield tag="773" ind1=" " ind2=" ">
    <subfield code="a">American Review of Public Administration</subfield>
  </datafield>
  <datafield tag="909" ind1=" " ind2=" ">
    <subfield code="a">109541</subfield>
  </datafield>
  <datafield tag="999" ind1=" " ind2=" ">
    <subfield code="c">109536</subfield>
    <subfield code="d">109536</subfield>
  </datafield>
  <datafield tag="952" ind1=" " ind2=" ">
    <subfield code="0">0</subfield>
    <subfield code="1">0</subfield>
    <subfield code="4">0</subfield>
    <subfield code="7">0</subfield>
    <subfield code="a">IIPA</subfield>
    <subfield code="b">IIPA</subfield>
    <subfield code="d">2018-07-19</subfield>
    <subfield code="h">Volume no: 45, Issue no: 5</subfield>
    <subfield code="p">AR110001</subfield>
    <subfield code="r">2018-07-19</subfield>
    <subfield code="w">2018-07-19</subfield>
    <subfield code="y">AR</subfield>
  </datafield>
</record>
