confoundvis 0.2.0

Bug fixes

Added the missing tests/testthat.R runner. In 0.1.0 the test files were shipped but never executed by R CMD check.
grid is now declared in Imports (it was used via grid::).
validate_confoundsens() now checks that lambda is nondecreasing within each level, so stacked multilevel paths no longer trigger a spurious warning.

sens_path_lm() computes the partial R-squared sensitivity path (Cinelli and Hazlett, 2020) directly from an lm fit, including weighted fits.
itcv_lm() computes the conditional and unconditional impact threshold (Frank, 2000; Frank et al., 2013) and the ITCV path.
covariate_impacts() benchmarks every observed covariate term (including multi-column factor terms for the partial R-squared metric) and returns a data frame that plot_sensitivity_love() and plot_sensitivity_contour() accept directly.
robustness_points() locates where a path reaches the null and where significance is lost; sens_report() turns these into a short plain-language report that states what the analysis cannot establish.

as_confoundsens() is now generic, with methods for data frames (as before), lm fits, and sensemakr objects.
from_sensemakr(), from_konfound(), and from_evalue() convert results from the ‘sensemakr’, ‘konfound’, and ‘EValue’ packages. These packages are only suggested; the adapters read documented fields and do not call them.
The test suite checks the computations against those packages when they are installed (adjusted estimates and standard errors, robustness values, conditional and unconditional ITCV, and E-values).

confoundsens objects gain an optional meta list (framework, labels, null value, critical value). Objects created by 0.1.0 remain valid.
plot_robustness_curve() uses axis labels from meta and gains reference to draw the null and critical values.
plot_sensitivity_love() takes its threshold from the "threshold" attribute of df when not supplied, and drops rows with missing impact.
plot_figure2_taylor_panels() is renamed plot_taylor_panels(); the old name is deprecated.
plot_reversal_cone() documentation now states that the display uses a stylized bilinear bias model and that the annotated share depends on the plotted ranges.
New vignette, “From a fitted model to a sensitivity report”, using the public darfur data and including a limitations section.