Replication methods to compute some basic statistic operations (means, standard deviations,
  frequency tables, percentiles, mean comparisons using weighted effect coding, generalized linear models,
  and linear multilevel models) in complex survey designs comprising multiple imputed or nested imputed
  variables and/or a clustered sampling structure which both deserve special procedures at least in
  estimating standard errors. See the package documentation for a more detailed description along with references.

Miscellaneous functions for data cleaning and data analysis of educational assessments. Includes functions for descriptive 
   analyses, character vector manipulations and weighted statistics. Mainly a lightweight dependency for the packages 'eatRep', 
   'eatGADS', 'eatPrep' and 'eatModel' (which will be subsequently submitted to 'CRAN').
   The function for defining (weighted) contrasts in weighted effect coding refers to
   te Grotenhuis et al. (2017) <doi:10.1007/s00038-016-0901-1>.
   Functions for weighted statistics refer to
   Wolter (2007) <doi:10.1007/978-0-387-35099-8>.

Expert Algorithm Verbal Autopsy assigns causes of death to 2016 WHO Verbal Autopsy Questionnaire data. odk2EAVA() converts data to a standard input format for cause of death determination building on the work of Thomas (2021) <https://cran.r-project.org/src/contrib/Archive/CrossVA/>. codEAVA() uses the presence and absence of signs and symptoms reported in the Verbal Autopsy interview to diagnose common causes of death. A deterministic algorithm assigns a single cause of death to each Verbal Autopsy interview record using a hierarchy of all common causes for neonates or children 1 to 59 months of age.

Fitting and testing multi-attribute probabilistic choice
  models, especially the Bradley-Terry-Luce (BTL) model (Bradley &
  Terry, 1952 <doi:10.1093/biomet/39.3-4.324>; Luce, 1959),
  elimination-by-aspects (EBA) models (Tversky, 1972 <doi:10.1037/h0032955>),
  and preference tree (Pretree) models (Tversky & Sattath, 1979
  <doi:10.1037/0033-295X.86.6.542>).