R.s.estimate.me: Calculates the proportion of treatment effect explained...

In laylaparast/Rsurrogate: Robust Estimation of the Proportion of Treatment Effect Explained by Surrogate Marker Information

Calculates the proportion of treatment effect explained correcting for measurement error in the surrogate marker

Description

This function calculates the proportion of treatment effect on the primary outcome explained by the treatment effect on a surrogate marker, correcting for measurement error in the surrogate marker. This function is intended to be used for a fully observed continuous outcome. The user must specify what type of estimation they would like (parametric or nonparametric estimation of the proportion explained, denoted by R) and what estimator they would like (see below for details).

Usage

R.s.estimate.me(sone, szero, yone, yzero, parametric = FALSE, estimator = "n", 
me.variance, extrapolate = TRUE, transform = FALSE, naive = FALSE, Ronly = TRUE)

Arguments

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.
parametric	TRUE or FALSE; indicates whether the user wants the parametric approach to be used (TRUE) or nonparametric (FALSE).
estimator	options are "d","q","n" for parametric and "q","n" for nonparametric; "d" stands for the disattenuated estimator, "q" stands for the SIMEX estimator with quadratic extrapolation, "n" stands for the SIMEX estimator with a nonlinear extrapolation.
me.variance	the variance of the measurement error; must be provided.
extrapolate	TRUE or FALSE; indicates whether the user wants to use extrapolation.
transform	TRUE or FALSE; indicates whether the user wants to use a transformation for the surrogate marker.
naive	TRUE or FALSE; indicates whether the user wants the naive estimate (not correcting for measurement error) to also be calculated
Ronly	TRUE or FALSE; indicates whether the user wants only R (and corresponding variance and confidence intervals) to be returned.

Details

Details can be found in Parast, L., Garcia, TP, Prentice, RL, Carroll, RJ (2019+). Robust Methods to Correct for Measurement Error when Evaluating a Surrogate Marker. Under Review.

Please email [e-mail] if you would like a copy of this article.

Value

A list is returned:

R.naive	the naive estimate of the proportion of treatment effect explained by the surrogate marker; only if naive = TRUE
R.naive.var	the estimated variance of the naive estimate of the proportion of treatment effect explained by the surrogate marker; only if naive = TRUE
R.naive.CI.normal	the 95% confidence interval using the normal approximation for the naive estimate of the proportion of treatment effect explained by the surrogate marker; only if naive = TRUE
R.naive.CI.fieller	the 95% confidence interval using Fieller's approach for the naive estimate of the proportion of treatment effect explained by the surrogate marker; only if naive = TRUE
B1star.naive	the naive estimate of the adjusted regression coefficient for treatment; only if naive = TRUE and Ronly = FALSE and parametric = TRUE
B1star.naive.var	the estimated variance of the naive estimate of the adjusted regression coefficient for treatment; only if naive = TRUE and Ronly = FALSE and parametric = TRUE
B1star.naive.CI.normal	the 95% confidence interval using the normal approximation for the naive estimate of the adjusted regression coefficient for treatment; only if naive = TRUE and Ronly = FALSE and parametric = TRUE
deltas.naive	the naive estimate of the residual treatment effect; only if naive = TRUE and Ronly = FALSE and parametric = FALSE
deltas.naive.var	the estimated variance of the naive estimate of the residual treatment effect; only if naive = TRUE and Ronly = FALSE and parametric = FALSE
deltas.naive.CI.normal	the 95% confidence interval using the normal approximation for the naive estimate of the residual treatment effect; only if naive = TRUE and Ronly = FALSE and parametric = FALSE
R.corrected.dis	the corrected disattenuated estimate of the proportion of treatment effect explained by the surrogate marker; only if parametric = TRUE and estimator ="d"
R.corrected.var.dis	the estimated variance of the corrected disattenuated estimate of the proportion of treatment effect explained by the surrogate marker; only if naive = TRUE
R.corrected.CI.normal.dis	the 95% confidence interval using the normal approximation for the corrected disattenuated estimate of the proportion of treatment effect explained by the surrogate marker; only if parametric = TRUE and estimator ="d"
R.corrected.CI.fieller.dis	the 95% confidence interval using Fieller's approach for the corrected disattenuated estimate of the proportion of treatment effect explained by the surrogate marker; only if parametric = TRUE and estimator ="d"
B1star.corrected.dis	the corrected disattenuated estimate of the adjusted regression coefficient for treatment; only if parametric = TRUE and estimator = "d" and Ronly = FALSE
B1star.corrected.var.dis	the estimated variance of the corrected disattenuated estimate of the adjusted regression coefficient for treatment; only if parametric = TRUE and estimator = "d" and Ronly = FALSE
B1star.corrected.CI.normal.dis	the 95% confidence interval using the normal approximation for the corrected disattenuated estimate of the adjusted regression coefficient for treatment; only if parametric = TRUE and estimator = "d" and Ronly = FALSE
R.corrected.q	the corrected SIMEX (quadratic) estimate of the proportion of treatment effect explained by the surrogate marker; only if estimator = "q"
R.corrected.var.q	the estimated variance of the corrected SIMEX (quadratic) estimate of the proportion of treatment effect explained by the surrogate marker; only if estimator = "q"
R.corrected.CI.normal.q	the 95% confidence interval using the normal approximation for the corrected SIMEX (quadratic) estimate of the proportion of treatment effect explained by the surrogate marker; only if estimator = "q"
R.corrected.CI.fieller.q	the 95% confidence interval using Fieller's approach for the corrected SIMEX (quadratic) estimate of the proportion of treatment effect explained by the surrogate marker; only if estimator = "q"
B1star.corrected.q	the corrected SIMEX (quadratic) estimate of the adjusted regression coefficient for treatment; only if estimator = "q" and Ronly = FALSE and parametric = TRUE
B1star.corrected.var.q	the estimated variance of the corrected SIMEX (quadratic) estimate of the adjusted regression coefficient for treatment; only if estimator = "q" and Ronly = FALSE and parametric = TRUE
B1star.corrected.CI.normal.q	the 95% confidence interval using the normal approximation for the corrected SIMEX (quadratic) estimate of the adjusted regression coefficient for treatment; only if estimator = "q" and Ronly = FALSE and parametric = TRUE
deltas.corrected.q	the corrected SIMEX (quadratic) estimate of the residual treatment effect; only if estimator = "q" and Ronly = FALSE and parametric = FALSE
deltas.corrected.var.q	the estimated variance of the corrected SIMEX (quadratic) estimate of the residual treatment effect; only if estimator = "q" and Ronly = FALSE and parametric = FALSE
deltas.corrected.CI.normal.q	the 95% confidence interval using the normal approximation for the corrected SIMEX (quadratic) estimate of the residual treatment effect; only if estimator = "q" and Ronly = FALSE and parametric = FALSE
R.corrected.nl	the corrected SIMEX (nonlinear) estimate of the proportion of treatment effect explained by the surrogate marker; only if estimator = "q"
R.corrected.var.nl	the estimated variance of the corrected SIMEX (nonlinear) estimate of the proportion of treatment effect explained by the surrogate marker; only if estimator = "q"
R.corrected.CI.normal.nl	the 95% confidence interval using the normal approximation for the corrected SIMEX (nonlinear) estimate of the proportion of treatment effect explained by the surrogate marker; only if estimator = "q"
R.corrected.CI.fieller.nl	the 95% confidence interval using Fieller's approach for the corrected SIMEX (nonlinear) estimate of the proportion of treatment effect explained by the surrogate marker; only if estimator = "q"
B1star.corrected.nl	the corrected SIMEX (nonlinear) estimate of the adjusted regression coefficient for treatment; only if estimator = "q" and Ronly = FALSE and parametric = TRUE
B1star.corrected.var.nl	the estimated variance of the corrected SIMEX (nonlinear) estimate of the adjusted regression coefficient for treatment; only if estimator = "q" and Ronly = FALSE and parametric = TRUE
B1star.corrected.CI.normal.nl	the 95% confidence interval using the normal approximation for the corrected SIMEX (nonlinear) estimate of the adjusted regression coefficient for treatment; only if estimator = "q" and Ronly = FALSE and parametric = TRUE
deltas.corrected.nl	the corrected SIMEX (nonlinear) estimate of the residual treatment effect; only if estimator = "q" and Ronly = FALSE and parametric = FALSE
deltas.corrected.var.nl	the estimated variance of the corrected SIMEX (nonlinear) estimate of the residual treatment effect; only if estimator = "q" and Ronly = FALSE and parametric = FALSE
deltas.corrected.CI.normal.nl	the 95% confidence interval using the normal approximation for the corrected SIMEX (nonlinear) estimate of the residual treatment effect; only if estimator = "q" and Ronly = FALSE and parametric = FALSE

Author(s)

Layla Parast

References

Parast, L., Garcia, TP, Prentice, RL, Carroll, RJ (2019+). Robust Methods to Correct for Measurement Error when Evaluating a Surrogate Marker. Under Review.

Examples

data(d_example)
names(d_example)
R.s.estimate.me(yone=d_example$y1, yzero=d_example$y0, sone=d_example$s1.a, szero=d_example$s0.a, 
parametric = TRUE, estimator = "d", me.variance = 0.5, naive= TRUE, Ronly = FALSE)
R.s.estimate.me(yone=d_example$y1, yzero=d_example$y0, sone=d_example$s1.a, szero=d_example$s0.a, 
parametric = TRUE, estimator = "q", me.variance = 0.5, naive= FALSE, Ronly = TRUE)
R.s.estimate.me(yone=d_example$y1, yzero=d_example$y0, sone=d_example$s1.a, szero=d_example$s0.a, 
parametric = FALSE, estimator = "q", me.variance = 0.5, naive= FALSE, Ronly = TRUE)

laylaparast/Rsurrogate documentation built on Sept. 28, 2022, 12:25 p.m.