Chapter 10: Missing Data Strategies

Introduction

Much Ado about Nothing?

Four Basic Approaches

Working with Complete Cases

Analysis with Sampling Weights

Imputation-based Methods

Recode

Informative Missing

Multivariate Normal Imputation

Multivariate SVD Imputation

Special Considerations for Time Series

Conclusion and a Note of Caution

References

Introduction

Chapter 9 illustrated several ways to detect missing observations within a data table and pointed ahead at some strategies for dealing with this common issue. This chapter illustrates four basic approaches to the problem. Unfortunately, there is no single strategy that dominates all others. The best approach depends on the goals of the project, the data types involved, and the domain knowledge ...

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