iv_sens | R Documentation |

`iv_sens`

performs a non-parametric, instrumental
variable sensitivity analysis on matched pairs following the logic of
the Neyman-Rubin framework for causal inference. The function supports
a variable-valued instrument.

iv_sens(Rt, Rc, Dt, Dc, Gamma = 6, GammaInc = 1)

`Rt,Rc` |
Vectors of observed response outcomes for matched treatment and control observations, respectively. |

`Dt,Dc` |
Vectors of observed doses for matched observations, respectively. This is level of dose encouraged by the instrument. |

`Gamma` |
Upper-bound on gamma parameter. |

`GammaInc` |
To set user specified increments for gamma parameter. |

Given matched pairs of observations on an instrument `Z`

,
which encourages dose `D`

, this function performs a Rosenbaum's bounds sensitivity analysis. Note that matching is done on levels of the instrument.

Returns an object of class `rbounds`

.

Luke Keele, University of Pennsylvania, luke.keele@gmail.com

Angrist, Joshua D., Imbens, Guido W., and Rubin, Donald B. (1996).
"Identification of Causal Effects Using Instrumental Variables."
*Journal of the American Statistical Association* 91/434, pp.
444–455.

Rosenbaum, Paul R. (1996). "Comment." *Journal of the American
Statistical Association* 91/434, pp. 465–468.

Rosenbaum, Paul R. (2002). *Observational Studies*.
Springer-Verlag.

Rosenbaum, Paul R. (2010). *Design of Observational Studies*.
Springer-Verlag.

See also `binarysens`

, `hlsens`

, `mcontrol`

data(angristlavy) # Example from Ch 5 of Design of Observational Studies #Extract Matched Outome Data Rt <- angristlavy$avgmath[angristlavy$z==1] Rc <- angristlavy$avgmath[angristlavy$z==0] #Extract Matched Doses #Doses Encouraged By Instrument - Here Class Size Dt <- angristlavy$clasz[angristlavy$z==1] Dc <- angristlavy$clasz[angristlavy$z==0] #Run Sensitivity Analsyis - Rank Sum Test iv_sens(Rc, Rt, Dc, Dt, Gamma=1.5, GammaInc=.01)

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