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SAMBA  

Selection and Misclassification Bias Adjustment for Logistic Regression Models
View on CRAN: Click here


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

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

Install by package version:
library("remotes")
install_version("SAMBA", "0.9.0")



Attach the package and use:
library("SAMBA")
Maintained by
Alexander Rix
[Scholar Profile | Author Map]
First Published: 2020-02-20
Latest Update: 2020-02-20
Description:
Health research using data from electronic health records (EHR) has gained popularity, but misclassification of EHR-derived disease status and lack of representativeness of the study sample can result in substantial bias in effect estimates and can impact power and type I error for association tests. Here, the assumed target of inference is the relationship between binary disease status and predictors modeled using a logistic regression model. 'SAMBA' implements several methods for obtaining bias-corrected point estimates along with valid standard errors as proposed in Beesley and Mukherjee (2020) , currently under review.
How to cite:
Alexander Rix (2020). SAMBA: Selection and Misclassification Bias Adjustment for Logistic Regression Models. R package version 0.9.0, https://cran.r-project.org/web/packages/SAMBA. Accessed 13 Apr. 2025.
Previous versions and publish date:
No previous versions
Other packages that cited SAMBA R package
View SAMBA citation profile
Other R packages that SAMBA depends, imports, suggests or enhances
Complete documentation for SAMBA
Functions, R codes and Examples using the SAMBA R package
Some associated functions: approxdist . nonlogistic . obsloglik . obsloglikEM . samba.df . sensitivity . 
Some associated R codes: approxdist.R . data.R . nonlogistic.R . obsloglik.R . obsloglikEM.R . sensitivity.R . utilityfunctions.R . variance.R .  Full SAMBA package functions and examples
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