future (>= 1.23.0), future.apply (>= 1.8.1), ggplot2 (>=
3.3.5), glmnet, gridExtra (>= 2.3), hrbrthemes, stats,

Jackknife(+) Predictive Intervals for Bayesian Models
person("Cory", "McCartan", , "cmccartan@g.harvard.edu", role = c("aut", "cre"),
comment = c(ORCID = "https://orcid.org/0000-0002-6251-669X"))
Provides functions to construct finite-sample calibrated predictive
intervals for Bayesian models, following the approach in Barber et al.
(2021) <doi:10.1214/20-AOS1965>. These intervals are calculated efficiently
using importance sampling for the leave-one-out residuals. By default,
the intervals will also reflect the relative uncertainty in the Bayesian
model, using the locally-weighted conformal methods of Lei et al. (2018)
<doi:10.1080/01621459.2017.1307116>.
rstanarm, brms, testthat (>= 3.0.0), ggplot2, knitr,
rmarkdown
Cory McCartan [aut, cre] (<https://orcid.org/0000-0002-6251-669X>)

Diagnostics for Confounding of Time-Varying and Other Joint
Exposures
c(person(given = "John W.", family = "Jackson",email = "john.jackson@jhu.edu", role = c("aut", "cre")),person(given =  "Erin", family = "Schnellinger",role = c("ctb")),person(given =  "Linda", family = "Valeri",role = c("ctb")))
Implements three covariate-balance diagnostics for time-varying confounding and selection-bias in complex longitudinal data, as described in Jackson (2016) <doi:10.1097/EDE.0000000000000547> and Jackson (2019) <doi:10.1093/aje/kwz136>. Diagnostic 1 assesses measured confounding/selection-bias, diagnostic 2 assesses exposure-covariate feedback, and diagnostic 3 assesses residual confounding/selection-bias after inverse probability weighting or propensity score stratification. All diagnostics appropriately account for exposure history, can be adapted to assess a particular depth of covariate history, and can be implemented in right-censored data. Balance assessments can be obtained for all times, selected-times, or averaged across person-time. The balance measures are reported as tables or plots. These diagnostics can be applied to the study of multivariate exposures including time-varying exposures, direct effects, interaction, and censoring.
John W. Jackson [aut, cre],
Erin Schnellinger [ctb],
Linda Valeri [ctb]