covarProfiles: Generates figure for 'Covariate Profiles' tab
In sanoke/hetviz: Treatment Effect Heterogeneity visualization

Description Usage Arguments Value See Also

covarProfiles() is an internal function that takes a dataset and returns a plot.

1 2	covarProfiles(ds, CPplotPts = TRUE, CPplotLines = TRUE, col.outcome, col.trt, col.ITE, col.grp, cols.covars, cols.cts, cols.ctg, simData)

`ds`	Any object that can be coerced into a `data.frame`, that contains data needed for plotting. This dataset is of a very specific structure, as defined within `dataCompat()`.
`CPplotPts`	A logical scalar. Should the plot include points?
`CPplotLines`	A logical scalar. Should the plot include connecting lines?
`col.outcome`	A scalar integer, indicating the column of `ds` that contains the outcome.
`col.trt`	A scalar integer, indicating the column of `ds` that contains the (binary) treatment.
`col.ITE`	A scalar integer, indicating the column of `ds` that contains the estimated ITEs.
`col.grp`	A scalar integer, indicating the column of `ds` that contains the grouping indicator.
`cols.covars`	A integer vector, indicating the columns of `ds` that contain covariates (i.e., excluding treatment, outcome, grouping var, and estimated ITE (if provided)).
`cols.cts`	A integer vector, indicating the columns of `ds` that contain continuous variables (including the treatment and outcome variables, if applicable).
`cols.ctg`	A integer vector, indicating the columns of `ds` that contain polytomous variables (including the treatment and outcome variables, if applicable).
`simData`	A logical scalar, indicating whether the data is the simple simulated data (`TRUE`) or is more complex (`FALSE`).

If both of the logical arguments are false, the output will be a plotly object containing an empty plot. Otherwise, the output will be a ggplot object containing the plot.

Other plotting functions: forestPlotGen.fewGroups, forestPlotGen.manyGroups, forestPlot, groupQuantiles, subgroupProfiles, vizByCovar, vizBySubgroup