Description Usage Arguments Details Value Author(s) References Examples
Estimates the calibration equation based on CV information
1 | calfun(x, y, CVx, CVy = CVx, lambda0 = 1)
|
x |
old VD measurements |
y |
reference (new) VD measurements |
CVx |
CV% of the old VD measurements |
CVy |
CV% of the new VD measurements |
lambda0 |
the CV ratio of the new vs old measurements |
Estimation of the calibration equation. It covers 4 scenarios: Only CVx is known; only CVy is known; both CVx and CVy are known; and Only the ratio of CVy to CVx is known.
coef |
estimated coefficients of the linear function |
se |
standard errors of the estimated coefficients |
lower CI |
the lower end of the 95% CI of the regression coefficients |
upper CI |
the upper end of the 95% CI of the regression coefficients |
Durazo-Arvizu, Ramon; Sempos, Chris; Tian, Lu
Tian L., Durazo-Arvizu R. A., Myers G., Brooks S., Sarafin K., and Sempos C. T. (2014), The estimation of calibration equations for variables with heteroscedastic measurement errors, Statist. Med., 33, pages 4420-4436
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