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  <titleInfo>
    <title>Introducing ANOVA and ANCOVA</title>
    <subTitle>a GLM approach</subTitle>
  </titleInfo>
  <name type="personal">
    <namePart>Rutherford, Andrew</namePart>
    <namePart type="date">1958-</namePart>
    <role>
      <roleTerm authority="marcrelator" type="text">creator</roleTerm>
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  <typeOfResource>text</typeOfResource>
  <genre authority="marc">bibliography</genre>
  <originInfo>
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      <placeTerm type="code" authority="marccountry">enk</placeTerm>
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    <place>
      <placeTerm type="text">London  ; Thousand Oaks, Calif</placeTerm>
    </place>
    <publisher>SAGE</publisher>
    <dateIssued>2001</dateIssued>
    <issuance>monographic</issuance>
  </originInfo>
  <language>
    <languageTerm authority="iso639-2b" type="code">eng</languageTerm>
  </language>
  <physicalDescription>
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    <extent>ix, 182 p. : ill. ; 25 cm.</extent>
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  <tableOfContents>Machine generated contents note: 1 AN INTRODUCTION TO GENERAL LINEAR MODELS: REGRESSION, ANALYSIS -- OF VARIANCE AND ANALYSIS OF COVARIANCE -- 1.1 Regression, analysis of variance and analysis of covariance -- 1.2 A pocket history of regression, ANOVA and ANCOVA -- 1.3 An outline of general linear models (GLMs) -- 1.3.1 Regression analysis -- 1.3.2 Analysis of variance -- 1.3.3 Analysis of covariance -- 1.4 The "general" in GLM -- 1.5 The "linear" in GLM -- 1.6 Least squares estimates -- 1.7 Fixed, random and mixed effects analyses -- 1.8 The benefits of a GLM approach to ANOVA and ANCOVA -- 1.9 The GLM presentation -- 1.10 Statistical packages for computers -- 2 TRADITIONAL AND GLM APPROACHES TO INDEPENDENT MEASURES SINGLE -- FACTOR ANOVA DESIGNS -- 2.1 Independent measures designs -- 2.1.1 Factors and independent variables -- 2.2 Traditional ANOVA for single factor designs -- 2.2.1 Variance -- 2.2.2 Example -- 2.3 GLM approaches to single factor ANOVA -- 2.3.1 Experimental design GLMs -- 2.3.2 Estimating effects by comparing full and reduced experimental -- design GLMs -- 2.3.3 Regression GLMs -- 2.3.4 Cell mean GLMs -- 2.3.5 Cell mean, regression and experimental desigh GLMs -- 3 GLM APPROACHES TO INDEPENDENT MEASURES FACTORIAL ANOVA -- DESIGNS -- 3.1 Factorial designs -- 3.2 Factor main effects and factor interactions -- 3.2.1 Estimating effects by comparing full and reduced experimental -- design GLMs -- 3.3 Regression GLMs for factorial ANOVA -- 3.3.1 Estimating main and interaction effects with regression GLMs -- 4 GLM APPROACHES TO REPEATED MEASURES DESIGNS -- 4.1 Related measures designs -- 4.2 Repeated measures designs -- 4.3 Order effect controls -- 4.3.1 Counterbalancing -- 4.3.2 Randomization -- 4.4 The GLM approach to single factor repeated measures designs -- 4.5 Estimating effects by comparing full and reduced single factor repeated -- measures design GLMs -- 4.6 Regression GLMs for single factor repeated measures designs -- 5 GLM APPROACHES TO FACTORIAL REPEATED MEASURES DESIGNS -- 5.1 Factorial related measures designs -- 5.2 The fully related factorial design GLM -- 5.3 Estimating effects by comparing full and reduced fully related factorial -- experimental design GLMs -- 5.4 Regression GLMs for the fully related factorial ANOVA -- 5.5 Mixed factorial ANOVA -- 5.6 Estimating effects by comparing full and reduced mixed factorial -- experimental design GLMs -- 5.7 Regression GLM for the mixed factorial ANOVA -- 6 THE GLM APPROACH TO ANCOVA -- 6.1 The nature of ANCOVA -- 6.2 Single factor independent measures ANCOVA designs -- 6.3 Estimating effects by comparing full and reduced single factor -- independent measures ANCOVA GLMs -- 6.4 Regression GLMs for the single factor independent measures -- ANCOVA -- 6.5 Other ANCOVA designs -- 6.5.1 Related measures ANCOVA designs -- 6.5.2 Mixed measures factorial ANCOVA -- 7 ASSUMPTIONS UNDERLYING ANOVA, TRADITIONAL ANCOVA AND GLMS -- 7.1 ANOVA and GLM assumptions -- 7.1.1 Independent measures -- 7.1.2 Related measures -- 7.1.3 Traditional ANCOVA -- 7.2 A strategy for checking ANOVA and traditional ANCOVA assumptions -- 7.3 Assumption checks and some assumption violation consequences -- 7.3.1 ANOVA and ANCOVA -- 7.3.2 Traditional ANCOVA -- 8 SOME ALTERNATIVES TO TRADITIONAL ANCOVA -- 8.1 Alternatives to traditional ANCOVA -- 8.2 The heterogeneous regression problem -- 8.3 The heterogeneous regression ANCOVA GLM -- 8.4 Single factor independent measures heterogeneous regression -- ANCOVA -- 8.5 Estimating heterogeneous regression ANCOVA effects -- 8.6 Regression GLMs for heterogeneous ANCOVA -- 8.7 Covariate-experimental condition relations -- 8.7.1 Multicollinearity -- 8.8 Other alternatives -- 8.8.1 Stratification (blocking) -- 8.8.2 Replacing the experimental conditions with the covariate -- 8.9 The role of ANCOVA -- 9 FURTHER ISSUES IN ANOVA AND ANCOVA -- 9.1 Power -- 9.1.1 Optimal experimental designs -- 9.1.2 Normality violations -- 9.1.3 Main effects and interactions -- 9.2 Error rate and the omnibus F-tests -- 9.3 Error rate and multiple comparisons -- 9.4 The role of the omnibus F-test -- REFERENCES -- INDEX.</tableOfContents>
  <note type="statement of responsibility">Andrew Rutherford.</note>
  <note>Index sheets need inserting.</note>
  <note>Includes bibliographical references (p. [173]-177) and index.</note>
  <subject authority="lcsh">
    <topic>Analysis of variance</topic>
  </subject>
  <subject authority="lcsh">
    <topic>Analysis of covariance</topic>
  </subject>
  <classification authority="lcc">QA279 .R88 2001</classification>
  <classification authority="ddc" edition="21">519.538 RUT</classification>
  <relatedItem type="series">
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      <title>ISM (London, England)</title>
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  <identifier type="isbn">0761951601</identifier>
  <identifier type="isbn">076195161X (pbk.)</identifier>
  <identifier type="lccn">2001270786</identifier>
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