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  <titleInfo>
    <title>GENERAL FACTORS IN EMPLOYEE ENGAGMENT SURVEYS</title>
  </titleInfo>
  <name>
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    <namePart>Mcdonald, Jordan C.</namePart>
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    <namePart>McAbee, Samuel</namePart>
  </name>
  <abstract>There is growing recognition of the need to model general factors within the context of job attitude constructs and their effects in the interpretation of employee engagement survey data. General factors are defined as latent variables that account for a substantial proportion of variance in multidimensional constructs and influence all subsets of items (Ree, Carretta &amp; Teachout, 2015). The bifactor model has gained increased attention for its advantages in modeling multidimensional constructs, including improved fit and enabling the examination of the unique contributions of the general and specific factors for prediction (Chen, Hayes, Carver, Laurenceau, &amp; Zhang, 2012; McAbee, Oswald, &amp; Connelly, 2014; Gignac, 2016; Reise, 2012). The aim of the current study was to apply the advantages of the bifactor model in the employee engagement survey context in predicting employee turnover compared to alternative factor models (i.e., correlated factors model). The current research consisted of two studies: the first was conducted to determine the factor model that balanced parsimony and plausibility by cross-validating the model’s generalizability with a different set of data sharing the same survey items. The second study compared the factors of the bifactor model—including the general factor—and the factors of the correlated factors model in predicting employee turnover. Accounting for the general factor in employee engagement surveys resulted in different factors being significantly to turnover compared to when the general factor was not modeled. Practical implications and directions for future research are discussed.</abstract>
  <note type="provenance">Submitted by Erma Thomas (thomase@iit.edu) on 2018-03-15T18:49:49Z No. of bitstreams: 1 etdadmin_upload_516016.zip: 1144718 bytes, checksum: 081414ccf6acf62d0447de330410e659 (MD5)</note>
  <note type="provenance">Made available in DSpace on 2018-03-15T18:49:49Z (GMT). No. of bitstreams: 1 etdadmin_upload_516016.zip: 1144718 bytes, checksum: 081414ccf6acf62d0447de330410e659 (MD5) Previous issue date: 2017-07</note>
  <note type="thesis">M.S. in Psychology, July 2017</note>
  <originInfo>
    <dateCaptured>2017</dateCaptured>
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  <originInfo>
    <dateCreated keyDate="yes">2017-07</dateCreated>
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  <identifier type="hdl">http://hdl.handle.net/10560/4207</identifier>
  <language>
    <languageTerm type="code" authority="rfc3066">en</languageTerm>
  </language>
  <subject>
    <topic>Bifactor model</topic>
  </subject>
  <subject>
    <topic>Employee attititudes</topic>
  </subject>
  <subject>
    <topic>Employee engagement</topic>
  </subject>
  <subject>
    <topic>Employee turnover</topic>
  </subject>
  <subject>
    <topic>General factor</topic>
  </subject>
  <subject>
    <topic>Survey methodology</topic>
  </subject>
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  <name type="corporate">
    <namePart>PSYCH / Institute of Psychology</namePart>
    <affiliation>Illinois Institute of Technology</affiliation>
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