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) <doi:10.1002/bimj.201700251>).

An extensible repository of accurate, up-to-date functions to
    score commonly used patient-reported outcome (PRO), quality of life
    (QOL), and other psychometric and psychological measures.
    'PROscorer', together with the 'PROscorerTools' package, is a system
    to facilitate the incorporation of PRO measures into research studies
    and clinical settings in a scientifically rigorous and reproducible
    manner.  These packages and their vignettes are intended to help
    establish and promote best practices for scoring PRO and PRO-like 
    measures in research.  The 'PROscorer' Instrument Descriptions vignette 
    contains descriptions of each instrument scored by 'PROscorer', complete 
    with references.  These instrument descriptions are suitable for inclusion 
    in formal study protocol documents, grant proposals, and manuscript Method
    sections.  Each 'PROscorer' function is composed of helper functions
    from the 'PROscorerTools' package, and users are encouraged to
    contribute new functions to 'PROscorer'.  More scoring functions are
    currently in development and will be added in future updates.

Provides a reliable and flexible toolbox to score 
    patient-reported outcome (PRO), Quality of Life (QOL), and other 
    psychometric measures. The guiding philosophy is that scoring errors can 
    be eliminated by using a limited number of well-tested, well-behaved 
    functions to score PRO-like measures. The workhorse of the package is 
    the 'scoreScale' function, which can be used to score most single-scale 
    measures. It can reverse code items that need to be reversed before 
    scoring and pro-rate scores for missing item data. Currently, three 
    different types of scores can be output: summed item scores, mean item 
    scores, and scores scaled to range from 0 to 100. The 'PROscorerTools' 
    functions can be used to write new functions that score more complex 
    measures. In fact, 'PROscorerTools' functions are the building blocks of 
    the scoring functions in the 'PROscorer' package (which is a repository 
    of functions that score specific commonly-used instruments). Users are 
    encouraged to use 'PROscorerTools' to write scoring functions for their 
    favorite PRO-like instruments, and to submit these functions for 
    inclusion in 'PROscorer' (a tutorial vignette will be added soon). The 
    long-term vision for the 'PROscorerTools' and 'PROscorer' packages is to 
    provide an easy-to-use system to facilitate the incorporation of PRO 
    measures into research studies in a scientifically rigorous and 
    reproducible manner. These packages and their vignettes are intended to 
    help establish and promote "best practices" for scoring and describing 
    PRO-like measures in research.