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We present R software packages RobustIV and controlfunctionIV for causalinference with possibly invalid instrumental variables. RobustIV focuses on thelinear outcome model. It implements the two-stage hard thresholding method toselect valid instrumental variables from a set of candidate instrumentalvariables and make inferences for the causal effect in both low- andhigh-dimensional settings. Furthermore, RobustIV implements thehigh-dimensional endogeneity test and the searching and sampling method, auniformly valid inference method robust to errors in instrumental variableselection. controlfunctionIV considers the nonlinear outcome model and makesinferences about the causal effect based on the control function method. Ourpackages are demonstrated using two publicly available economic data setstogether with applications to the Framingham Heart Study.

RobustIV and controlfunctionIV: Causal Inference for Linear and Nonlinear Models with Invalid Instrumental Variables