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surveyCV  

Cross Validation Based on Survey Design
View on CRAN: Click here


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

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

Install by package version:
library("remotes")
install_version("surveyCV", "0.2.0")



Attach the package and use:
library("surveyCV")
Maintained by
Jerzy Wieczorek
[Scholar Profile | Author Map]
First Published: 2022-01-10
Latest Update: 2022-03-15
Description:
Functions to generate K-fold cross validation (CV) folds and CV test error estimates that take into account how a survey dataset's sampling design was constructed (SRS, clustering, stratification, and/or unequal sampling weights). You can input linear and logistic regression models, along with data and a type of survey design in order to get an output that can help you determine which model best fits the data using K-fold cross validation. Our paper on "K-Fold Cross-Validation for Complex Sample Surveys" by Wieczorek, Guerin, and McMahon (2022) <doi:10.1002/sta4.454> explains why differing how we take folds based on survey design is useful.
How to cite:
Jerzy Wieczorek (2022). surveyCV: Cross Validation Based on Survey Design. R package version 0.2.0, https://cran.r-project.org/web/packages/surveyCV. Accessed 10 Apr. 2025.
Previous versions and publish date:
0.1.1 (2022-01-10 18:50)
Other packages that cited surveyCV R package
View surveyCV citation profile
Other R packages that surveyCV depends, imports, suggests or enhances
Complete documentation for surveyCV
Functions, R codes and Examples using the surveyCV R package
Some associated functions: NSFG_data . NSFG_data_everypreg . cv.svy . cv.svydesign . cv.svyglm . folds.svy . folds.svydesign . pipe . surveyCV . 
Some associated R codes: cv.svy.R . cv.svydesign.R . cv.svyglm.R . data.R . folds.svy.R . folds.svydesign.R . surveyCV.R . utils-pipe.R .  Full surveyCV package functions and examples
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