| calibrate_anim {sensitivityCalibration} | R Documentation |
Make the dynamic calibration plot.
Description
This is another main function in the package. For a given p and the border of the sensitivity parameters (lambda, delta), a calibration plot is made for each (lambda, delta) pair on the border.
Usage
calibrate_anim(border, q, u, p, degree, xmax, ymax, data_matched)
Arguments
border |
Border or frontier of the sensitivity parameters for a fixed p. |
q |
Number of matched covariates plus treatment. |
u |
Unmeasured confounder; u = c(1,0) if the unmeasured confounder is assumed to be binary. |
p |
The probability vector corresponding to u; p = c(0.5, 0.5) if the unmeasured confounder is assumed to be Bernoulli(0.5). |
degree |
Degree of freedom of the spline fit for the boundary. |
xmax |
Maximum xlim of the plot. |
ymax |
Maximum ylim of the plot. |
data_matched |
The matched dataset. |
Details
border is the dataframe returned by the function find_border. It has to contain at least (k+1) different lambda/delta pairs in order to fit a smoothing spline with k dfs.
Examples
data(NHANES_blood_lead_small_matched)
attach(NHANES_blood_lead_small_matched)
# Prepare the border
lambda_vec = c(seq(0.1,1.9,0.1), 2.2, 2.5, 3, 3.5, 4)
delta_vec = c(7.31, 5.34, 4.38, 3.76, 3.18, 2.87, 2.55, 2.36, 2.16, 1.99, 1.86,
1.74, 1.63, 1.54, 1.44, 1.40, 1.31, 1.28, 1.22, 1.08, 0.964, 0.877, 0.815, 0.750)
border = data.frame(lambda_vec, delta_vec)
calibrate_anim(border, 9, c(1,0), c(0.5,0.5), 10, 5, 3.5, NHANES_blood_lead_small_matched)
detach(NHANES_blood_lead_small_matched)