• Summary
  • Contents
  • Subject index

In this important new Handbook, the editors have gathered together a range of leading contributors to introduce the theory and practice of multilevel modeling.

The Handbook establishes the connections in multilevel modeling, bringing together leading experts from around the world to provide a roadmap for applied researchers linking theory and practice, as well as a unique arsenal of state-of-the-art tools. It forges vital connections that cross traditional disciplinary divides and introduces best practice in the field.

Part I establishes the framework for estimation and inference, including chapters dedicated to notation, model selection, fixed and random effects, and causal inference; Part II develops variations and extensions, such as nonlinear, semiparametric and latent class models; Part III includes discussion of missing data and robust methods, assessment of fit and ...

The Choice between Fixed and Random Effects
The choice between fixed and random effects
ZacTownsendNew York University, USA
JackBuckleyNational Center for Education Statistics and New York University, USA
MasatakaHaradaNew York University, USA
MarcA.ScottNew York University, USA
5.1 Introduction

In prior chapters, group-specific effects were assumed to be drawn from a distribution, typically Gaussian. In applied research in the social and behavioral sciences, economics, public health, public policy, and many other fields, alternatives to this choice are often made, with the most common being the “fixed effects” approach. In its most basic formulation, group-specific intercepts are modeled using indicator variables, effectively making them open parameters in the model and not assigning them a distributional form. The choice between random and fixed effects has implications for the interpretation of parameter estimates and for ...

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