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glmMisrep  

Generalized Linear Models Adjusting for Misrepresentation
View on CRAN: Click here


Download and install glmMisrep package within the R console
Install from CRAN:
install.packages("glmMisrep")

Install from Github:
library("remotes")
install_github("cran/glmMisrep")

Install by package version:
library("remotes")
install_version("glmMisrep", "0.1.1")



Attach the package and use:
library("glmMisrep")
Maintained by
Patrick Rafael
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2024-03-26
Latest Update: 2024-03-26
Description:
Fit Generalized Linear Models to continuous and count outcomes, as well as estimate the prevalence of misrepresentation of an important binary predictor. Misrepresentation typically arises when there is an incentive for the binary factor to be misclassified in one direction (e.g., in insurance settings where policy holders may purposely deny a risk status in order to lower the insurance premium). This is accomplished by treating a subset of the response variable as resulting from a mixture distribution. Model parameters are estimated via the Expectation Maximization algorithm and standard errors of the estimates are obtained from closed forms of the Observed Fisher Information. For an introduction to the models and the misrepresentation framework, see Xia et. al., (2023) .
How to cite:
Patrick Rafael (2024). glmMisrep: Generalized Linear Models Adjusting for Misrepresentation. R package version 0.1.1, https://cran.r-project.org/web/packages/glmMisrep. Accessed 12 Nov. 2024.
Previous versions and publish date:
0.1.0 (2024-03-26 10:00)
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