# Diagnostics of instrumental variable analysis ```r iv.diagnosis(Y, D, Z, X) iv.diagnosis.plot(output, bias.ratio = TRUE, base_size = 15, text_size = 5) ``` ## Arguments - `Y`: A numeric vector of outcomes. - `D`: A vector of endogenous variables. - `Z`: A vector of instruments. - `X`: A vector, matrix or data frame of (exogenous) covariates. - `output`: Output from `iv.diagnosis`. - `bias.ratio`: Add bias ratios (text) to the plot? - `base_size`: size of the axis labels - `text_size`: size of the text (bias ratios) ## Returns a list or data frame - **x.mean1**: Mean of X under Z = 1 (reported if Z is binary) - **x.mean0**: Mean of X under Z = 0 (reported if Z is binary) - **coef**: OLS coefficient of X ~ Z (reported if Z is not binary) - **se**: Standard error of OLS coefficient (reported if Z is not binary) - **p.val**: p-value of the independence of Z and X (Fisher's test if both are binary, logistic regression if Z is binary, linear regression if Z is continuous) - **stand.diff**: Standardized difference (reported if Z is binary) - **bias.ratio**: Bias ratio - **bias.amplify**: Amplification of bias ratio - **bias.ols**: Bias of OLS - **bias.2sls**: Bias of two stage least squares) ## Functions * `iv.diagnosis.plot()`: IV diagnostic plot ## Examples ```r n <- 10000 Z <- rbinom(n, 1, 0.5) X <- data.frame(matrix(c(rnorm(n), rbinom(n * 5, 1, 0.5)), n)) D <- rbinom(n, 1, plogis(Z + X[, 1] + X[, 2] + X[, 3])) Y <- D + X[, 1] + X[, 2] + rnorm(n) print(output <- iv.diagnosis(Y, D, Z, X)) iv.diagnosis.plot(output) Z <- rnorm(n) D <- rbinom(n, 1, plogis(Z + X[, 1] + X[, 2] + X[, 3])) Y <- D + X[, 1] + X[, 2] + rnorm(n) print(output <- iv.diagnosis(Y, D, Z, X)) ## stand.diff is not reported iv.diagnosis.plot(output) ``` ## References * Baiocchi, M., Cheng, J., & Small, D. S. (2014). Instrumental variable methods for causal inference. Statistics in Medicine, 33(13), 2297-2340. * Jackson, J. W., & Swanson, S. A. (2015). Toward a clearer portrayal of confounding bias in instrumental variable applications. Epidemiology, 26(4), 498. * Zhao, Q., & Small, D. S. (2018). Graphical diagnosis of confounding bias in instrumental variable analysis. Epidemiology, 29(4), e29--e31. ## Author(s) Qingyuan Zhao

iv.diagnosis function