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cprobit  

Conditional Probit Model for Analysing Continuous Outcomes
View on CRAN: Click here


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

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

Install by package version:
library("remotes")
install_version("cprobit", "1.0.2")



Attach the package and use:
library("cprobit")
Maintained by
Ning Yilin
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2020-05-27
Latest Update: 2020-05-27
Description:
Implements the three-step workflow for robust analysis of change in two repeated measurements of continuous outcomes, described in Ning et al. (in press), "Robust estimation of the effect of an exposure on the change in a continuous outcome", BMC Medical Research Methodology.
How to cite:
Ning Yilin (2020). cprobit: Conditional Probit Model for Analysing Continuous Outcomes. R package version 1.0.2, https://cran.r-project.org/web/packages/cprobit. Accessed 10 Oct. 2026.
Previous versions and publish date:
No previous versions
Other packages that cited cprobit R package
View cprobit citation profile
Other R packages that cprobit depends, imports, suggests or enhances
Complete documentation for cprobit
Functions, R codes and Examples using the cprobit R package
Some associated functions: bg_variability . compile_est . cprobit . cprobit_step1 . estimate_sd_error . geom_mean . get_v . make_design_mat . profile_llh . update_estimate . 
Some associated R codes: cprobit.R .  Full cprobit package functions and examples
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