PACKT (406)
Text Book 교재용원서 (674)
컴퓨터공학 (797)
컴퓨터 일반도서 (551)
전기,전자공학 (699)
기계공학 (188)
재료공학 (31)
에너지공학 (65)
의용공학 (37)
생명과학 (224)
물리학 (424)
지구과학 (74)
천문학 (38)
수학 (102)
통계학 (45)
경영학 (40)
산업공학 (12)
사회복지학 (5)
심리학 (247)
교육학 (1)
화학 (4)
기타 (61)
특가할인도서 (86)

> > 컴퓨터공학 > 데이터마이닝

이미지를 클릭하시면 큰 이미지를 보실 수 있습니다.
Flexible Imputation of Missing Data, Second Edition
출판사 : CRC
저 자 : Stef van Buuren
ISBN : 9781138588318
발행일 : 2018-7
도서종류 : 외국도서
발행언어 : 영어
페이지수 : 416
판매가격 : 59,000원
판매여부 : 재고확인요망
주문수량 : [+]수량을 1개 늘입니다 [-]수량을 1개 줄입니다

My Wish List 에 저장하기
   Flexible Imputation of Missing Data, Second Edition 목차

Table of Contents

Introduction

Multiple imputation

Univariate missing data

Multivariate missing data

Analysis of imputed data

Imputation in practice

Multilevel multiple imputation

Individual Causal Effects

Measurement issues

Selection issues

Longitudinal data

Conclusion
   도서 상세설명   


Summary

Missing data pose challenges to real-life data analysis. Simple ad-hoc fixes, like deletion or mean imputation, only work under highly restrictive conditions, which are often not met in practice. Multiple imputation replaces each missing value by multiple plausible values. The variability between these replacements reflects our ignorance of the true (but missing) value. Each of the completed data set is then analyzed by standard methods, and the results are pooled to obtain unbiased estimates with correct confidence intervals. Multiple imputation is a general approach that also inspires novel solutions to old problems by reformulating the task at hand as a missing-data problem.

This is the second edition of a popular book on multiple imputation, focused on explaining the application of methods through detailed worked examples using the MICE package as developed by the author. This new edition incorporates the recent developments in this fast-moving field.

This class-tested book avoids mathematical and technical details as much as possible: formulas are accompanied by verbal statements that explain the formula in accessible terms. The book sharpens the reader’s intuition on how to think about missing data, and provides all the tools needed to execute a well-grounded quantitative analysis in the presence of missing data.

  교육용 보조자료   
작성된 교육용 보조자료가 없습니다.