{"title":"Analyzing data with systematic bias","authors":"M. Zampetakis","doi":"10.1145/3572885.3572890","DOIUrl":null,"url":null,"abstract":"In many data analysis problems, we only have access to biased data due to some systematic bias of the data collection procedure. In this letter, we present a general formulation of systematic bias in data as well as our recent results on how to handle two very fundamental types of systematic bias that arise frequently in econometric studies: truncation bias and self-selection bias.","PeriodicalId":56237,"journal":{"name":"ACM SIGecom Exchanges","volume":"20 1","pages":"55 - 63"},"PeriodicalIF":0.6000,"publicationDate":"2022-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"ACM SIGecom Exchanges","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/3572885.3572890","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS","Score":null,"Total":0}
引用次数: 0
Abstract
In many data analysis problems, we only have access to biased data due to some systematic bias of the data collection procedure. In this letter, we present a general formulation of systematic bias in data as well as our recent results on how to handle two very fundamental types of systematic bias that arise frequently in econometric studies: truncation bias and self-selection bias.