Replication methods to compute some basic statistic operations (means, standard deviations,
  frequency tables, percentiles and generalized linear models) in complex survey designs comprising multiple
  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>.

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>).

Package implements entropy balancing, a data preprocessing procedure described in Hainmueller (2008, <doi:10.1093/pan/mpr025>) that allows users to reweight a dataset such that the covariate distributions in the reweighted data satisfy a set of user specified moment conditions. This can be useful to create balanced samples in observational studies with a binary treatment where the control group data can be reweighted to match the covariate moments in the treatment group. Entropy balancing can also be used to reweight a survey sample to known characteristics from a target population.

Estimate ecosystem metabolism in a Bayesian framework for
  individual water quality monitoring stations with continuous dissolved
  oxygen time series. A mass balance equation is used that provides
  estimates of parameters for gross primary production, respiration,
  and gas exchange. Methods adapted from Grace et al. (2015)
  <doi:10.1002/lom3.10011> and Wanninkhof (2014) <doi:10.4319/lom.2014.12.351>.
  Details in Beck et al. (2024) <doi:10.1002/lom3.10620>.