Package: ICEinfer 1.3

Bob Obenchain

ICEinfer: Incremental Cost-Effectiveness Inference using Two Unbiased Samples

Given two unbiased samples of patient level data on cost and effectiveness for a pair of treatments, make head-to-head treatment comparisons by (i) generating the bivariate bootstrap resampling distribution of ICE uncertainty for a specified value of the shadow price of health, lambda, (ii) form the wedge-shaped ICE confidence region with specified confidence fraction within [0.50, 0.99] that is equivariant with respect to changes in lambda, (iii) color the bootstrap outcomes within the above confidence wedge with economic preferences from an ICE map with specified values of lambda, beta and gamma parameters, (iv) display VAGR and ALICE acceptability curves, and (v) illustrate variation in ICE preferences by displaying potentially non-linear indifference(iso-preference) curves from an ICE map with specified values of lambda, beta and either gamma or eta parameters.

Authors:Bob Obenchain

ICEinfer_1.3.tar.gz
ICEinfer_1.3.tar.gz(r-4.5-noble)ICEinfer_1.3.tar.gz(r-4.4-noble)
ICEinfer_1.3.tgz(r-4.4-emscripten)ICEinfer_1.3.tgz(r-4.3-emscripten)
ICEinfer.pdf |ICEinfer.html✨
ICEinfer/json (API)

# Install 'ICEinfer' in R:
install.packages('ICEinfer', repos = c('https://cran.r-universe.dev', 'https://cloud.r-project.org'))

Peer review:

Datasets:
  • dpunc - Output list object of class ICEuncrt for the High Uncertainty numerical example in the ICEinfer package, data(dulxparx).
  • dpwdg - Output list object of class ICEwedge for the High Uncertainty example, data
  • dulxparx - Data for the High Uncertainty numerical example of Obenchain et al.
  • fluoxpin - Data from a double-blind clinical trial comparing fluoxetine plus pindolol with fluoxetine alone
  • fluoxtca - Cost-Effectiveness data for 1242 MDD patients from Marketscan(SM) claims database
  • sepsis - Artificial data.frame of 7 characteristics of patients treated for septic shock

This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.

1.76 score 19 scripts 230 downloads 3 mentions 8 exports 1 dependencies

Last updated 4 years agofrom:74fb42bb85. Checks:OK: 1 NOTE: 1. Indexed: no.

TargetResultDate
Doc / VignettesOKOct 24 2024
R-4.5-linuxNOTEOct 24 2024

Exports:ICEaliceICEcolorICEepmapICEomegaICEprefICEscaleICEuncrtICEwedge

Dependencies:lattice

Readme and manuals

Help Manual

Help pageTopics
ICE Statistical Inference and Economic Preference VariationICEinfer-package
Output list object of class ICEuncrt for the High Uncertainty numerical example in the ICEinfer package, data(dulxparx).dpunc
Output list object of class ICEwedge for the High Uncertainty example, data(dulxparx)dpwdg
Data for the High Uncertainty numerical example of Obenchain et al. (2005)dulxparx
Data from a double-blind clinical trial comparing fluoxetine plus pindolol with fluoxetine alonefluoxpin
Cost-Effectiveness data for 1242 MDD patients from Marketscan(SM) claims databasefluoxtca
Functions to compute and display ICE Acceptability CurvesICEalice
Compute Preference Colors for Outcomes within a Bootstrap Confidence WedgeICEcolor
Set Parameter Values defining ICE Economic Preference MapsICEepmap ICEomega
Compute ICE Economic Preference Scores from Numeric Cost and Effe MeasuresICEpref
ICEscale() functions compute or print ICE Statistical Inference Summary Statistics relative to choice for the numerical value of the Shadow Price of Health, lambdaICEscale
Compute Bootstrap Distribution of ICE Uncertainty for given Shadow Price of Health, lambdaICEuncrt
Equivariant Wedge-Shaped ICE Region with Confidence Level from 0.50 to 0.99ICEwedge
Display Economic Preferences for ICE Outcomes within a Bootstrap Confidence Wedgeplot.ICEcolor
Display Indifference Curves on a standardized ICE Economic Preference Mapplot.ICEepmap
Display Scatter for a possibly Transformed Bootstrap Distribution of ICE Uncertaintyplot.ICEuncrt
Summary Statistics for a possibly Transformed Bootstrap Distribution of ICE Uncertaintyprint.ICEuncrt
Artificial data.frame of 7 characteristics of patients treated for septic shocksepsis