登入選單
返回Google圖書搜尋
Missing Data
Paul D. Allison
出版SAGE Publications, 2001-08-13
主題Social Science / ResearchReference / ResearchPsychology / Research & Methodology
ISBN14522079099781452207902
URLhttp://books.google.com.hk/books?id=LJB2AwAAQBAJ&hl=&source=gbs_api
EBookSAMPLE
註釋Sooner or later anyone who does statistical analysis runs into problems with missing data in which information for some variables is missing for some cases. Why is this a problem? Because most statistical methods presume that every case has information on all the variables to be included in the analysis. Using numerous examples and practical tips, this book offers a nontechnical explanation of the standard methods for missing data (such as listwise or casewise deletion) as well as two newer (and, better) methods, maximum likelihood and multiple imputation. Anyone who has been relying on ad-hoc methods that are statistically inefficient or biased will find this book a welcome and accessible solution to their problems with handling missing data.