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    <title>Regression models for categorical and count data</title>
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    <namePart>Martin, Peter.</namePart>
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    <publisher>SAGE Publications</publisher>
    <dateIssued>2021</dateIssued>
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  <abstract>This text provides practical guidance on conducting regression analysis on categorical and count data. Step by step and supported by lots of helpful graphs, it covers both the theoretical underpinnings of these methods as well as their application, giving you the skills needed to apply them to your own research. It offers guidance on: * Using logistic regression models for binary, ordinal, and multinomial outcomes * Applying count regression, including Poisson, negative binomial, and zero-inflated models * Choosing the most appropriate model to use for your research * The general principles of good statistical modelling in practice Part of The SAGE Quantitative Research Kit, this book will give you the know-how and confidence needed to succeed on your quantitative research journey. --</abstract>
  <note type="statement of responsibility">by Peter Martin.</note>
  <note>Includes bibliographical references and index.</note>
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    <topic>Regression analysis</topic>
    <topic>Mathematical models</topic>
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    <topic>Data processing</topic>
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  <subject authority="lcsh">
    <topic>Quantitative research</topic>
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  <subject authority="lcsh">
    <topic>Regression analysis</topic>
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  <subject authority="lcsh">
    <topic>Mathematical models</topic>
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    <topic>Regression Analysis</topic>
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    <topic>Models, Theoretical</topic>
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  <subject authority="rvm">
    <topic>Recherche quantitative</topic>
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  <subject authority="rvm">
    <topic>Analyse de régression</topic>
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  <subject authority="rvm">
    <topic>Modèles mathématiques</topic>
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    <topic>mathematical models</topic>
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    <topic>Mathematical models</topic>
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  <subject authority="fast">
    <topic>Quantitative research</topic>
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  <subject authority="fast">
    <topic>Regression analysis</topic>
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