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.
|Author||Sebastien Cossin [aut, cre], Clement Bader [ctb], Morgane Donadel [ctb], Aline Maillard [ctb], Antoine Benard [ctb]|
|Date of publication||2016-10-02 13:18:36|
|Maintainer||Sebastien Cossin <email@example.com>|
create_object_evpi_decrease: Create an object evpi_decrease
create_object_inmb: Create an object INMB
create_object_inmb_direct: Create an object INMB_DIRECT
create_object_lambda: Create an object lambda
create_object_pop: Create an object POP
create_object_var_inmb: Create an object var_inmb
create_object_var_inmb_diff: Create an object var_inmb_diff
create_object_var_inmb_direct: Create an object var_inmb_direct
EBASS-internal: Internal mypackage Functions
EVPI_DECREASE: A Reference Class to represent the EVPI
gamma_risk: Function to estimate the gamma risk
graph_gain_n: Explain the estimated sample size calculated
INMB: A Reference Class to represent the INMB (Incremental Net...
INMB_DIRECT: A Reference Class to represent the INMB (Incremental Net...
Lambda: A Reference Class to represent the lambda value
POP: A Reference Class to represent the target population
sample_size: Function to calculate the estimated sample size based on the...
VAR_INMB: A Reference Class to represent the Hypothetical variance of...
VAR_INMB_DIFF: A Reference Class to represent the variance of the...
VAR_INMB_DIRECT: A Reference Class to represent the theoretical standard...