EBASS: Sample Size Calculation Method for Cost-Effectiveness Studies Based on Expected Value of Perfect Information

We propose a new sample size calculation method for trial-based cost-effectiveness analyses. Our strategy is based on the value of perfect information that would remain after the completion of the study.

Install the latest version of this package by entering the following in R:
install.packages("EBASS")
AuthorSebastien Cossin [aut, cre], Clement Bader [ctb], Morgane Donadel [ctb], Aline Maillard [ctb], Antoine Benard [ctb]
Date of publication2016-10-02 13:18:36
MaintainerSebastien Cossin <cossin.sebastien@gmail.com>
LicenseGPL-3
Version0.1
https://github.com/scossin/EBASS

View on CRAN

Functions

check_1 Man page
check_entier Man page
check_heritage Man page
check_positif Man page
create_object_evpi_decrease Man page
create_object_inmb Man page
create_object_inmb_direct Man page
create_object_lambda Man page
create_object_pop Man page
create_object_var_inmb Man page
create_object_var_inmb_diff Man page
create_object_var_inmb_direct Man page
EVPI_DECREASE Man page
gamma_risk Man page
graph_gain_n Man page
INMB Man page
INMB_DIRECT Man page
Lambda Man page
POP Man page
sample_size Man page
VAR_INMB Man page
VAR_INMB_DIFF Man page
VAR_INMB_DIRECT Man page

Questions? Problems? Suggestions? or email at ian@mutexlabs.com.

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