Restrictions.BinBin {Surrogate}

Examine restrictions in \bold{\pi}_{f} under different montonicity assumptions for binary S and T

Description

The function Restrictions.BinBin gives an overview of the restrictions in \bold{\pi}_{f} under different assumptions regarding montonicity when both S and T are binary.

Usage

Restrictions.BinBin(pi1_1_, pi1_0_, pi_1_1, pi_1_0, pi0_1_, pi_0_1)

Arguments

pi1_1_

A scalar that contains P(T=1,S=1|Z=0), i.e., the proability that S=T=1 when under treatment Z=0.

pi1_0_

A scalar that contains P(T=1,S=0|Z=0).

pi_1_1

A scalar that contains P(T=1,S=1|Z=1).

pi_1_0

A scalar that contains P(T=1,S=0|Z=1).

pi0_1_

A scalar that contains P(T=0,S=1|Z=0).

pi_0_1

A scalar that contains P(T=0,S=1|Z=1).

Value

An overview of the restrictions for the freely varying parameters imposed by the data is provided

Author(s)

Wim Van der Elst, Ariel Alonso, & Geert Molenberghs

References

Alonso, A., Van der Elst, W., & Molenberghs, G. (2014). Validation of surrogate endpoints: the binary-binary setting from a causal inference perspective.

See Also

MarginalProbs

Examples

Restrictions.BinBin(pi1_1_=0.262, pi0_1_=0.135, pi1_0_=0.286, 
pi_1_1=0.637, pi_1_0=0.078, pi_0_1=0.127)