Package: metaggR
Type: Package
Title: Calculate the Knowledge-Weighted Estimate
Version: 0.3.0
Authors@R: 
    c(person(given = "Ville",
             family = "Satopää",
             email = "ville.satopaa@gmail.com",
             role = c("aut", "cre", "cph")),
      person(given = "Asa",
             family = "Palley",
             role = "aut"))
Description: 
    According to a phenomenon known as "the wisdom of the crowds," 
    combining point estimates from multiple judges often provides a 
    more accurate aggregate estimate than using a point estimate from
    a single judge. However, if the judges use shared information in 
    their estimates, the simple average will over-emphasize this common
    component at the expense of the judges’ private information. 
    Asa Palley & Ville Satopää (2021) "Boosting the Wisdom of Crowds
    Within a Single Judgment Problem: Selective Averaging Based on Peer Predictions"
    <https://papers.ssrn.com/sol3/Papers.cfm?abstract_id=3504286> proposes
    a procedure for calculating a weighted average of the judges’ individual
    estimates such that resulting aggregate estimate appropriately combines
    the judges' collective information within a single estimation problem. 
    The authors use both simulation and data from six experimental studies
    to illustrate that the weighting procedure outperforms existing averaging-like
    methods, such as the equally weighted average, trimmed average, and median.
    This aggregate estimate -- know as "the knowledge-weighted estimate" --
    inputs a) judges' estimates of a continuous outcome (E) and 
    b) predictions of others' average estimate of this outcome (P).  
    In this R-package, the function knowledge_weighted_estimate(E,P) 
    implements the knowledge-weighted estimate. Its use is illustrated
    with a simple stylized example and on real-world experimental data. 
License: GPL-2
Copyright: (c) Ville Satopaa
Encoding: UTF-8
LazyData: true
RoxygenNote: 7.1.1
Imports: MASS, stats
Suggests: knitr, rmarkdown, testthat (>= 3.0.0)
VignetteBuilder: knitr
Config/testthat/edition: 3
Depends: R (>= 4.1)
NeedsCompilation: no
Packaged: 2022-04-25 09:44:27 UTC; ville.satopaa
Author: Ville Satopää [aut, cre, cph],
  Asa Palley [aut]
Maintainer: Ville Satopää <ville.satopaa@gmail.com>
Repository: CRAN
Date/Publication: 2022-04-25 10:00:02 UTC
Built: R 4.1.3; ; 2023-04-17 13:49:05 UTC; windows
