mclogit: Multinomial Logit Models, with or without Random Effects or Overdispersion Technical documentation
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Technical documentationΒΆ

  • The relation between baseline logit and conditional logit models
  • The IWLS algorithm used to fit conditional logit models
  • Approximate Inference for Multinomial Logit Models with Random Effects
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Table of Contents

  • Publications
  • Data Sets
  • Software
    • Packages
      • memisc: Management of Survey Data and Presentation of Analysis Results
      • mclogit: Multinomial Logit Models, with or without Random Effects or Overdispersion
        • mclogit on CRAN
        • Baseline-category logit models
        • Conditional logit models
        • Random effects in baseline logit models and conditional logit models
        • Documentation of the Package
          • Manual pages
          • Index
          • Technical documentation
            • The relation between baseline logit and conditional logit models
            • The IWLS algorithm used to fit conditional logit models
            • Approximate Inference for Multinomial Logit Models with Random Effects
        • References
      • munfold: Metric Multidimensional Unfolding in R
      • mpred: Generic Predictive Margins
      • manifestos: Spatial Modelling of Party Manifestos (and other political texts)
      • iimm: Improved Inference for Multilevel Models with Few Clusters
      • EMfit: An Infrastructure for Latent Variable Model Fitting using EM Algorithms
      • RKernel: Yet another R kernel for Jupyter
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