Datasets from most recent CCIIO DIY entry
in a tidy format. These support the Centers for Medicare and Medicaid
Services' (CMS) risk adjustment Do-It-Yourself (DIY) process, which allows
health insurance issuers to calculate member risk profiles under the Health
and Human Services-Hierarchical Condition Categories (HHS-HCC) regression
model. This regression model is used to calculate risk adjustment transfers.
Risk adjustment is a selection mitigation program implemented under the
Patient Protection and Affordable Care Act (ACA or Obamacare) in the USA.
Under the ACA, health insurance issuers submit claims data to CMS	in order
for CMS to calculate a risk score under the HHS-HCC regression model.
However, CMS does not inform issuers of their average risk score until after
the data submission deadline. These data sets can be used by issuers to
calculate their average risk score mid-year. More information about risk
adjustment and the HHS-HCC model can be found here:
<https://www.cms.gov/mmrr/Articles/A2014/MMRR2014_004_03_a03.html>.

person(given = "Emi",
family = "Tanaka",
role = c("aut", "cre", "cph"),
email = "dr.emi.tanaka@gmail.com",
comment = c(ORCID = "0000-0002-1455-259X"))
A system to facilitate designing comparative experiments using the
grammar of experimental designs <https://emitanaka.org/edibble-book/>.
An experimental design is treated as an intermediate, mutable object that is
built progressively by fundamental experimental components like units, treatments, and their relation.
magrittr, rlang, vctrs, tibble, cli, pillar, tidyselect (>=
1.0.0), nestr, stats, AlgDesign, dae, R6
testthat (>= 3.0.0), rmarkdown, openxlsx, visNetwork
Emi Tanaka [aut, cre, cph] (<https://orcid.org/0000-0002-1455-259X>)

testthat (>= 3.0.0), rmarkdown, openxlsx, visNetwork, covr

Bayesian Estimation of an Exploratory Deterministic Input, Noisy
and Gate Model
c(
person("James Joseph", "Balamuta",
email = "balamut2@illinois.edu",
role = c("aut", "cre", "cph"),
comment = c(ORCID = "0000-0003-2826-8458")),
person("Steven Andrew", "Culpepper",
email = "sculpepp@illinois.edu",
role = c("aut", "cph"),
comment = c(ORCID = "0000-0003-4226-6176")
),
person("Jeffrey A.", "Douglas",
email = "jeffdoug@illinois.edu",
role = c("aut"))
)
Perform a Bayesian estimation of the exploratory
deterministic input, noisy and gate (EDINA)
cognitive diagnostic model described by Chen et al. (2018)
<doi:10.1007/s11336-017-9579-4>.
James Joseph Balamuta [aut, cre, cph]
(<https://orcid.org/0000-0003-2826-8458>),
Steven Andrew Culpepper [aut, cph]
(<https://orcid.org/0000-0003-4226-6176>),
Jeffrey A. Douglas [aut]