Loading...
Please wait, while we are loading the content...
Similar Documents
Regression Calibration for Covariate Measurement Error
| Content Provider | Scilit |
|---|---|
| Author | Shaw, Pamela A. |
| Copyright Year | 2021 |
| Description | Regression calibration is one of the first statistical methods introduced to address covariate measurement error. Despite its simplicity and approximate nature in non-linear models, regression calibration persists today as perhaps the single most popular method to address covariate measurement error in regression models. In this chapter, we present the method of regression calibration. We illustrate the method with a few examples, which will highlight both its typical use and some of the challenges that can arise. We will discuss the performance of regression calibration in comparison to other methods. We will conclude the chapter with a few extensions to regression calibration, which improve its performance in challenging settings, such as those with a high degree of non-linearity. We also discuss some applications of regression calibration to address error in the outcome. Book Name: Handbook of Measurement Error Models |
| Related Links | https://api.taylorfrancis.com/content/chapters/edit/download?identifierName=doi&identifierValue=10.1201/9781315101279-7&type=chapterpdf |
| Ending Page | 136 |
| Page Count | 10 |
| Starting Page | 127 |
| DOI | 10.1201/9781315101279-7 |
| Language | English |
| Publisher | Informa UK Limited |
| Publisher Date | 2021-09-28 |
| Access Restriction | Open |
| Subject Keyword | Book Name: Handbook of Measurement Error Models Models Address Covariate Covariate Measurement Error Regression Calibration Chapter |
| Content Type | Text |
| Resource Type | Chapter |
