Statistical Methods for Handling Incomplete Data - Jae Kwang Kim,Jun Shao
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Along with many examples, this text covers the most up-to-date statistical theories and computational methods for analyzing incomplete data. It presents a thorough treatment of statistical theories of likelihood-based inference with missing data. It also discusses numerous computational techniques and theories on imputation and extensively covers methods involving propensity score weighting, nonignorable mi ... Pilns apraksts
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Aprašymas
Along with many examples, this text covers the most up-to-date statistical theories and computational methods for analyzing incomplete data. It presents a thorough treatment of statistical theories of likelihood-based inference with missing data. It also discusses numerous computational techniques and theories on imputation and extensively covers methods involving propensity score weighting, nonignorable missing data, longitudinal missing data, survey sampling, and statistical matching. Some of the research ideas introduced can be developed further for specific applications.
Vairāk informācijas
| Autors | Jae Kwang Kim, Jun Shao |
|---|---|
| Izdevējs | Taylor & Francis |
| Izlaides gads | 2013 |
| Vāka tips | Cietais vāks |
| EAN | 9781439849637 |