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RISCA (version 0.8.2)

Causal Inference and Prediction in Cohort-Based Analyses

Description

We propose numerous functions for cohort-based analyses, either for prediction or causal inference. For causal inference, it includes Inverse Probability Weighting and G-computation for marginal estimation of an exposure effect when confounders are expected. We deal with binary outcomes, times-to-events (Le Borgne, 2016, ), competing events (Trebern-Launay, 2018, ), and multi-state data (Gillaizeau, 2018, ). For multistate data, semi-Markov model with interval censoring (Foucher, 2008, ) may be considered and we propose the possibility to consider the excess of mortality related to the disease compared to reference lifetime tables (Gillaizeau, 2017, ). For predictive studies, we propose a set of functions to estimate time-dependent receiver operating characteristic (ROC) curves with the possible consideration of right-censoring times-to-events or the presence of confounders (Le Borgne, 2018, ). Finally, several functions are available to assess time-dependent ROC curves (Combescure, 2017, ) or survival curves (Combescure, 2014, ) from aggregated data.

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Version

Install

install.packages('RISCA')

Monthly Downloads

430

Version

0.8.2

License

GPL (>= 2)

Maintainer

Y. Foucher

Last Published

April 5th, 2020

Functions in RISCA (0.8.2)

dataDIVAT1

A First Sample From The DIVAT Data Bank.
dataDIVAT5

The Aggregated Kidney Graft Survival Stratified By The 1-year Serum Creatinine.
auc

Area Under ROC Curve From Sensitivities And Specificities.
expect.utility2

Cut-Off Estimation Of A Prognostic Marker (Two Groups Are observed).
dataCSL

CSL Liver Chirrosis Data.
dataDIVAT2

A Second Sample From the DIVAT Data Bank.
dataHepatology

The Data Extracted From The Meta-Analysis By Cabibbo et al. (2010).
gc.survival

Marginal Effect for Censored Outcome by G-computation.
dataDIVAT3

A Third Sample From the DIVAT Data Bank.
plot.roc

Plot Method for 'roc' Objects
ipw.log.rank

Log-Rank Test for Adjusted Survival Curves.
markov.3states

3-State Time-Inhomogeneous Markov Model
semi.markov.3states.ic

3-State Semi-Markov Model With Interval-Censored Data
dataDIVAT4

A Fourth Sample From the DIVAT Data Bank.
expect.utility1

Cut-Off Estimation Of A Prognostic Marker (Only One Observed Group).
markov.3states.rsadd

3-state Relative Survival Markov Model with Additive Risks
gc.logistic

Marginal Effect for Binary Outcome by G-computation.
fr.ratetable

Expected Mortality Rates of the General French Population
semi.markov.3states.rsadd

3-State Relative Survival Semi-Markov Model With Additive Risks
gc.sl.binary

Marginal Effect for Binary Outcome by Super Learned G-computation.
survival.summary

Summary Survival Curve From Aggregated Data
dataKTFS

A Sixth Sample Of The DIVAT Cohort.
ipw.survival

Adjusted Survival Curves by Using IPW.
roc.net

Net Time-Dependent ROC Curves With Right Censored Data.
dataKi67

The Aggregated Data Published By de Azambuja et al. (2007).
lrs.multistate

Likelihood Ratio Statistic to Compare Embedded Multistate Models
differentiation

Numerical Differentiation with Finite Differences.
markov.4states

4-State Time-Inhomogeneous Markov Model
survival.summary.strata

Summary Survival Curve And Comparison Between Strata.
semi.markov.4states.rsadd

4-State Relative Survival Semi-Markov Model With Additive Risks
rmst

Restricted Mean Survival Times.
markov.4states.rsadd

4-state Relative Survival Markov Model with Additive Risks
mixture.2states

Horizontal Mixture Model for Two Competing Events
rein.ratetable

Expected Mortality Of French Patients With ESKD.
semi.markov.4states

4-State Semi-Markov Model
lines.roc

Add Lines to a ROC Plot
usa.ratetable

Expected Mortality Rates Of The General United States Population.
plot.survival

Plot Method for 'survival' Objects
roc.binary

ROC Curves For Binary Outcomes.
roc.summary

Summary ROC Curve For Aggregated Data.
pred.mixture.2states

Cumulative Incidence Function Form Horizontal Mixture Model With Two Competing Events
semi.markov.3states

3-State Semi-Markov Model
roc.time

Time-Dependent ROC Curves With Right Censored Data.