Statistical matching, or data fusion, merges microdata from sample surveys. The goal is to create a synthetic file with a merged set of variables. A typical scenario is that variables (X,Y) are collected in Survey A, and variables (X,Z) are collected in Survey B. Statistical matching creates a synthetic microdata file from the Survey A and Survey B data, with values of X, Y, and Z on each record. Uncertainty occurs during statistical matching because information is lacking about the distribution of (Y,Z). A method to exhibit the uncertainty in estimates due to the statistical matching procedure is to allow a variety of assumptions to be made about the distribution of (Y,Z), carry out statistical matching to create a dataset corresponding to each assumption, and then assess the variation in estimates made from the group of datasets created by this procedure. This book describes innovations of previous work by Kadane (1978) and Rubin (1986) that implements the method correctly. Practitioners in the fields of applied statistics and microsimulation modeling who carry out statistical matching will find the methodologies described in this book to be useful for their work.
"synopsis" may belong to another edition of this title.
Seller: GreatBookPrices, Columbia, MD, U.S.A.
Condition: New. Seller Inventory # 8286662-n
Seller: PBShop.store US, Wood Dale, IL, U.S.A.
PAP. Condition: New. New Book. Shipped from UK. THIS BOOK IS PRINTED ON DEMAND. Established seller since 2000. Seller Inventory # L0-9783639218879
Seller: Rarewaves.com USA, London, LONDO, United Kingdom
Paperback. Condition: New. Seller Inventory # LU-9783639218879
Quantity: Over 20 available
Seller: PBShop.store UK, Fairford, GLOS, United Kingdom
PAP. Condition: New. New Book. Delivered from our UK warehouse in 4 to 14 business days. THIS BOOK IS PRINTED ON DEMAND. Established seller since 2000. Seller Inventory # L0-9783639218879
Quantity: Over 20 available
Seller: Ria Christie Collections, Uxbridge, United Kingdom
Condition: New. In. Seller Inventory # ria9783639218879_new
Quantity: Over 20 available
Seller: Chiron Media, Wallingford, United Kingdom
Paperback. Condition: New. Seller Inventory # 6666-IUK-9783639218879
Quantity: 10 available
Seller: GreatBookPricesUK, Woodford Green, United Kingdom
Condition: New. Seller Inventory # 8286662-n
Quantity: Over 20 available
Seller: moluna, Greven, Germany
Kartoniert / Broschiert. Condition: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Autor/Autorin: Moriarity ChrisChris Moriarity, PhD: Studied Statistics at The George Washington University. Mathematical Statistician at the National Center for Health Statistics, Hyattsville, MD USA.Statistical matching, or data fusion, merge. Seller Inventory # 4968211
Quantity: Over 20 available
Seller: preigu, Osnabrück, Germany
Taschenbuch. Condition: Neu. Statistical Properties of Statistical Matching | Data Fusion Algorithm | Chris Moriarity | Taschenbuch | Einband - flex.(Paperback) | Englisch | 2009 | VDM Verlag Dr. Müller | EAN 9783639218879 | Verantwortliche Person für die EU: OmniScriptum GmbH & Co. KG, Bahnhofstr. 28, 66111 Saarbrücken, info[at]akademikerverlag[dot]de | Anbieter: preigu. Seller Inventory # 101397359
Seller: AHA-BUCH GmbH, Einbeck, Germany
Taschenbuch. Condition: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - Statistical matching, or data fusion, merges microdata from sample surveys. The goal is to create a synthetic file with a merged set of variables. A typical scenario is that variables (X,Y) are collected in Survey A, and variables (X,Z) are collected in Survey B. Statistical matching creates a synthetic microdata file from the Survey A and Survey B data, with values of X, Y, and Z on each record. Uncertainty occurs during statistical matching because information is lacking about the distribution of (Y,Z). A method to exhibit the uncertainty in estimates due to the statistical matching procedure is to allow a variety of assumptions to be made about the distribution of (Y,Z), carry out statistical matching to create a dataset corresponding to each assumption, and then assess the variation in estimates made from the group of datasets created by this procedure. This book describes innovations of previous work by Kadane (1978) and Rubin (1986) that implements the method correctly. Practitioners in the fields of applied statistics and microsimulation modeling who carry out statistical matching will find the methodologies described in this book to be useful for their work. Seller Inventory # 9783639218879