sensitivityCalibration (version 0.0.1)

calibrate_anim: 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

# NOT RUN {
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)
# }