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Instrumental variables, bootstrapping, and generalized linear models AgEcon
Hardin, James W.; Schmiediche, Henrik; Carroll, Raymond J..
This paper discusses and illustrates the qvf command for fitting generalized linear models. The differences between this new command and Stata’s glm command are highlighted. One of the most notable features of the qvf command is its ability to include instrumental variables. This functionality was added specifically to address measurement error but may be utilized by the user for other purposes. The qvf command was developed in the C-language using Stata’s new plugin features and executes much faster than the glm ado-file.
Tipo: Journal Article Palavras-chave: Measurement error; Instrumental variables; Murphy–Topel; Bootstrap; Generalized linear models; Research Methods/ Statistical Methods.
Ano: 2003 URL: http://purl.umn.edu/116178
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The regression-calibration method for fitting generalized linear models with additive measurement error AgEcon
Hardin, James W.; Schmiediche, Henrik; Carroll, Raymond J..
This paper discusses and illustrates the method of regression calibration. This is a straightforward technique for fitting models with additive measurement error. We present this discussion in terms of generalized linear models (GLMs) following the notation defined in Hardin and Carroll (2003). Discussion will include specified measurement error, measurement error estimated by replicate error-prone proxies, and measurement error estimated by instrumental variables. The discussion focuses on software developed as part of a small business innovation research (SBIR) grant from the National Institutes of Health (NIH).
Tipo: Journal Article Palavras-chave: Regression calibration; Measurement error; Instrumental variables; Replicate measures; Generalized linear models; Research Methods/ Statistical Methods.
Ano: 2003 URL: http://purl.umn.edu/116180
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The simulation extrapolation method for fitting generalized linear models with additive measurement error AgEcon
Hardin, James W.; Schmiediche, Henrik; Carroll, Raymond J..
We discuss and illustrate the method of simulation extrapolation for fitting models with additive measurement error. We present this discussion in terms of generalized linear models (GLMs) following the notation defined in Hardin and Carroll (2003). As in Hardin, Schmiediche, and Carroll (2003), our discussion includes specified measurement error and measurement error estimated by replicate error-prone proxies. In addition, we discuss and illustrate three extrapolant functions.
Tipo: Journal Article Palavras-chave: Simulation extrapolation; Measurement error; Instrumental variables; Replicate measures; Generalized linear models; Research Methods/ Statistical Methods.
Ano: 2003 URL: http://purl.umn.edu/116184
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