# confint.txshift: Confidence Intervals for Counterfactual Mean Under Stochastic... In txshift: Efficient Estimation of the Causal Effects of Stochastic Interventions

## Description

Confidence Intervals for Counterfactual Mean Under Stochastic Intervention

## Usage

 ```1 2``` ```## S3 method for class 'txshift' confint(object, parm = seq_len(object\$psi), level = 0.95, ...) ```

## Arguments

 `object` An object of class `txshift`, as produced by invoking the function `txshift`, for which a confidence interval is to be computed. `parm` A `numeric` vector indicating indices of `object\$est` for which to return confidence intervals. `level` A `numeric` indicating the level of the confidence interval to be computed. `...` Other arguments. Not currently used.

## Details

Compute confidence intervals for estimates produced by `txshift`.

## Value

A named `numeric` vector containing the parameter estimate from a `txshift` object, alongside lower and upper Wald-style confidence intervals at a specified coverage level.

## Examples

 ``` 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19``` ```set.seed(429153) n_obs <- 100 W <- replicate(2, rbinom(n_obs, 1, 0.5)) A <- rnorm(n_obs, mean = 2 * W, sd = 1) Y <- rbinom(n_obs, 1, plogis(A + W + rnorm(n_obs, mean = 0, sd = 1))) txout <- txshift( W = W, A = A, Y = Y, delta = 0.5, estimator = "tmle", g_fit_args = list( fit_type = "hal", n_bins = 5, grid_type = "equal_mass", lambda_seq = exp(-1:-9) ), Q_fit_args = list( fit_type = "glm", glm_formula = "Y ~ ." ) ) confint(txout) ```

txshift documentation built on Oct. 23, 2020, 8:27 p.m.