detect_idiosyncratic function

detect_idiosyncratic

Test for systematic treatment effect heterogeneity using Fisherian permutation inference methods.

detect_idiosyncratic(formula, data, interaction.formula,
  control.formula, plugin, tau.hat, test.stat, te.vec, B, gamma, grid.gamma,
  grid.size, return.matrix, na.rm, n.cores, verbose, ...)

Arguments

• formula: An object of class formula, as in lm(), such as Y ~ Z with only the treatment variable on the right-hand side.
• data: A data.frame, tbl_df, or data.table with the input data.
• interaction.formula: A right-sided formula with pre-treatment covariates to model treatment effects for on the right hand side, such as ~ x1 + x2 + x3. Defaultis NULL (no interactions modeled)
• control.formula: A right-sided formula with pre-treatment covariates to adjust for on the right hand side, such as ~ x1 + x2 + x3. Default is NULL (no variables adjusted for)
• plugin: Whether to calculate the plug-in p-value without sweeping over range of possible treatment effect magnitudes. Default is FALSE.
• tau.hat: The value of the plug-in treatment effect. Default is sample average treatment effect.
• test.stat: Test statistic function to use on the data. Default is shifted Kolmogorov-Smirnov statistic, potentially with covariate adjustment depending on passed arguments. test.stat can be a string name for a test statistic function, or the function itself.
• te.vec: Vector of taus to examine if you want to override generating ones automatically. Default is NULL.
• B: Number of permutations to take. Default is 500.
• gamma: How wide of a CI to make around tau-hat for search. Default is 0.0001.
• grid.gamma: Parameter to govern where the grid points are sampled. Bigger values means more samples towards the estimated tau-hat. Default is 100*gamma.
• grid.size: Number of points in the grid. Default is 151.
• return.matrix: Whether to return the matrix of all the imputed statistics. Default is FALSE.
• na.rm: A logical flag indicating whether to list-wise delete missing data. The function will report an error if missing data exist. Default is FALSE.
• n.cores: Number of cores to use to parallelize permutation step. Default is 1.
• verbose: Whether to print out progress bar when fitting and other diagnostics. Default is TRUE.
• ...: Extra arguments passed to the generate.permutations function and test.stat functions.

Returns

If plug-in, the value of the test and the associated p-value. If not, a list with the value of the test statistic on the observed data, the value of the CI-adjusted p-value, the plug-in p-value, and other information on the test.

Examples

Z <- rep(c(0, 1), 100)
tau <- 4
Y <- ifelse(Z, rnorm(100, tau), rnorm(100, 0))
df <- data.frame(Y=Y, Z=Z)
tst <- detect_idiosyncratic(Y ~ Z, df, B = 50, grid.size = 50)