View source: R/Functions_Rsurrogate.R
calculate.var.np | R Documentation |
calculates closed form variance estimate for R; used in R function that corrects for measurement error
calculate.var.np(s1, s0, y1, y0, extrapolate = TRUE)
sone |
numeric vector or matrix; surrogate marker for treated observations, assumed to be continuous. If there are multiple surrogates then this should be a matrix with n_1 (number of treated observations) rows and n.s (number of surrogate markers) columns. |
szero |
numeric vector; surrogate marker for control observations, assumed to be continuous.If there are multiple surrogates then this should be a matrix with n_0 (number of control observations) rows and n.s (number of surrogate markers) columns. |
yone |
numeric vector; primary outcome for treated observations, assumed to be continuous. |
yzero |
numeric vector; primary outcome for control observations, assumed to be continuous. |
extrapolate |
TRUE or FALSE; indicates whether the user wants to use extrapolation. |
total |
matrix needed for variance calculation |
psionly |
matrix needed for variance calculation |
Layla Parast
Parast, L., McDermott, M., Tian, L. (2016). Robust estimation of the proportion of treatment effect explained by surrogate marker information. Statistics in Medicine, 35(10):1637-1653.
Parast, L., Garcia, TP, Prentice, RL, Carroll, RJ (2019+). Robust Methods to Correct for Measurement Error when Evaluating a Surrogate Marker. Under Review.
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