Description Usage Arguments Value References Examples
ivbds
is used to estimate bounds on various effects using instrumental variables.
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y |
outcome of interest. |
a |
binary treatment. |
z |
binary instrument. |
x |
covariate matrix. |
nsplits |
integer number of sample splits for nuisance estimation. If nsplits=1, sample splitting is not used, and nuisance functions are estimated on full sample (in which case validity of SEs/CIs requires empirical process conditions). Otherwise must have nsplits>1. |
sl.lib |
algorithm library for SuperLearner. Default library includes "earth", "gam", "glm", "glmnet", "glm.interaction", "mean", "ranger", "rpart". |
project01 |
should the estimated compliance score be projected to space respecting 0-1 bounds and monotonicity? |
A list containing the following components:
res |
estimates/SEs/CIs/p-values for local average treatment effect E(Y(a=1)-Y(a=0)|A(z=1)>A(z=0)), as well as IV strength and sharpness. |
nuis |
subject-specific estimates of nuisance functions (i.e., IV propensity score and treatment/outcome regressions) |
ifvals |
matrix of estimated influence function values. |
(Also see references for function ate
)
Angrist JD, Imbens GW, Rubin DB (1996). Identification of causal effects using instrumental variables. Journal of the American Statistical Association.
Abadie A (2003). Semiparametric instrumental variable estimation of treatment response models. Journal of Econometrics.
Kennedy EH, Balakrishnan S, G'Sell M (2017). Complier classification with sharp instrumental variables. Working Paper.
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