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PROreg (version 1.3)

Patient Reported Outcomes Regression Analysis

Description

It offers a wide variety of techniques, such as graphics, recoding, or regression models, for a comprehensive analysis of patient-reported outcomes (PRO). Especially novel is the broad range of regression models based on the beta-binomial distribution useful for analyzing binomial data with over-dispersion in cross-sectional, longitudinal, or multidimensional response studies (see Najera-Zuloaga J., Lee D.-J. and Arostegui I. (2019) ).

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Version

Install

install.packages('PROreg')

Monthly Downloads

2,616

Version

1.3

License

GPL

Maintainer

Josu Najera-Zuloaga

Last Published

March 13th, 2024

Functions in PROreg (1.3)

summary.BBest

Summarizes a BBest class model.
summary.BBmm

Summarizes a BBmm class model.
print.summary.BBmm

Print a summary.BBmm class model.
print.BBreg

Print a BBreg class model.
print.summary.BBest

Print a summary.BBest class model.
summary.BBreg

Summarizes a BBreg class model.
print.summary.BBreg

Print a summary.BBreg class model.
print.BBmm

Print a BBmm class model.
BB

The Beta-Binomial Distribution
BBest

Estimation of the parameters of a beta-binomial distribution
EDpro

Eating Disorders patient-reported outcome data.
BIest

Estimation of the parameters of a binomial distribution with optional dispersion parameter.
BBreg

Fit a beta-binomial logistic regression model
SF36rec

Short Form-36 Health Survey recode
BBmm

Beta-binomial mixed-effects model
print.BBest

Print a BBest class model.
BI

The Binomial distribution with optional Dispersion Parameter
HRQoLplot

Spider plot of the dimensions of the Short Form-36 Health Survey