calibrate_anim: Make the dynamic calibration plot.

In sensitivityCalibration: A Calibrated Sensitivity Analysis for Matched Observational Studies

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)

sensitivityCalibration documentation built on May 2, 2019, 1:07 p.m.