cicc_plot {ciccr} | R Documentation |
Plotting Upper Bounds on Relative and Attributable Risk
Description
Plots upper bounds on relative and attributable risk
Usage
cicc_plot(
results,
parameter = "RR",
sampling = "cc",
save_plots = FALSE,
file_name = Sys.Date(),
plots_ctl = 0.3
)
Arguments
results |
estimation results from either cicc_RR or cicc_AR |
parameter |
'RR' for relative risk; 'AR' for attributable risk (default = 'RR') |
sampling |
'cc' for case-control sampling; 'cp' for case-population sampling (default = 'cc') |
save_plots |
TRUE if the plots are saved as pdf files; FALSE if not (default = FALSE) |
file_name |
the pdf file name to save the plots (default = Sys.Date()) |
plots_ctl |
value to determine the topleft position of the legend in the figure a large value makes the legend far away from the confidence intervals (default = 0.3) |
Value
A X-Y plot where the X axis shows the range of p from 0 to p_upper and the Y axis depicts both point estimates and the upper end point of the one-sided confidence intervals.
References
Jun, S.J. and Lee, S. (2020). Causal Inference under Outcome-Based Sampling with Monotonicity Assumptions. https://arxiv.org/abs/2004.08318.
Examples
# use the ACS_CC dataset included in the package.
y = ciccr::ACS_CC$topincome
t = ciccr::ACS_CC$baplus
x = ciccr::ACS_CC$age
results = cicc_RR(y, t, x)
cicc_plot(results)