Logga in

Sök "missing data"

Graham, John W. - Missing Data, e-bok

Missing Data

Graham, John W.

115,00€

Practical Issues Relating to Analysis with Missing Data: Avoiding and Troubleshooting Problems
John W. Graham
9. Dealing with the Problem of Having Too Many Variables in the Imputation Model
John W. Graham, M. Lee

Tsiatis, Anastasios A. - Semiparametric Theory and Missing Data, e-bok

Semiparametric Theory and Missing Data

Tsiatis, Anastasios A.

76,95€

Locally Efficient Estimators for Coarsened-Data Semiparametric Models
12. Approximate Methods for Gaining Efficiency
13. Double-Robust Estimator of the Average Causal Treatment Effect
14. Multiple Imputation: A Frequentist Perspective

DRM-restrictions
Printing:

Kenward, Michael - Missing Data in Clinical Studies, e-bok

Missing Data in Clinical Studies

Kenward, Michael

88,90€

Missing Data in Clinical Studies provides a comprehensive account of the problems arising when data from clinical and related studies are incomplete, and presents the reader with approaches to effectively address

Longford, Nicholas T. - Missing Data and Small-Area Estimation, e-bok

Missing Data and Small-Area Estimation

Longford, Nicholas T.

69,25€

Table of contents
Part I. Missing data
1. Prologue
2. Describing incompleteness
3. Single imputation and related methods
4. Multiple imputation
5. Case studies
Part II. Small-area estimation
6. Introduction
7. Models for small areas
8. Using auxiliary information
9. Using small-area estimators
10.

Bouza-Herrera, Carlos N. - Handling Missing Data in Ranked Set Sampling, e-bok

Handling Missing Data in Ranked Set Sampling

Bouza-Herrera, Carlos N.

58,15€

Table of contents
1. Missing Observations and Data Quality Improvement
Carlos N. Bouza-Herrera
2. Sampling Using Ranked Sets: Basic Concepts
Carlos N. Bouza-Herrera
3. The Non-response Problem: Subsampling Among the Non-respondents
Carlos N. Bouza-Herrera
4. Imputation of the Missing Data
Carlos

Montanari, Angela - Data Science, e-bok

Data Science

Montanari, Angela

118,65€

Benchmarking for Clustering Methods Based on Real Data: A Statistical View
Anne-Laure Boulesteix, Myriam Hatz
7. Representable Hierarchical Clustering Methods for Asymmetric Networks
Gunnar Carlsson, Facundo Mémoli, Alejandro Ribeiro, Santiago Segarra
8.