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cprobit (version 1.0.2)

Conditional Probit Model for Analysing Continuous Outcomes

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.

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Version

Install

install.packages('cprobit')

Monthly Downloads

196

Version

1.0.2

License

LGPL-3

Maintainer

Ning Yilin

Last Published

May 27th, 2020

Functions in cprobit (1.0.2)

make_design_mat

Inpernal function: construct design matrix without the intercept term.
estimate_sd_error

Inpernal function: estimate the SD of error terms in the difference model
compile_est

Inpernal function: generate commonly used summary statistics for estimates.
update_estimate

Inpernal function: update Step 1 estimates to obtain linear exposure effect on (transformed) outcome
get_v

Inpernal function: compute difference in the (transformed) outcome
geom_mean

Inpernal function: compute geometric mean of a positive variable
profile_llh

Inpernal function: profile log-likelihood of lambda
cprobit

Apply the three-step workflow for the analysis of two repeated outcomes from each subject
bg_variability

Inpatient blood glucose data for 1200 patients
cprobit_step1

Inpernal function: step 1 of the proposed workflow