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quantreg (version 5.98)

QTECox: Function to obtain QTE from a Cox model

Description

Computes quantile treatment effects comparable to those of crq model from a coxph object.

Usage

QTECox(x, smooth = TRUE)

Value

taus

points of evaluation of the QTE.

QTE

matrix of QTEs, the ith column contains the QTE for the ith covariate effect. Note that there is no intercept effect. see plot.summary.crqs for usage.

Arguments

x

An object of class coxph produced by coxph.

smooth

Logical indicator if TRUE (default) then Cox survival function is smoothed.

Author

Roger Koenker Stephen Portnoy & Tereza Neocleous

Details

Estimates of the Cox QTE, \(\frac{dQ(t|x)}{dx_{j}}\) at \(x=\bar{x}\), can be expressed as a function of t as follows:

$$\frac{dQ(t|x)}{dx_{j}}=\frac{dt}{dx_{j}}\frac{dQ(t|x)}{dt}$$

The Cox survival function, \(S(y|x)=\exp \{-H_{0}(y)\exp (b^{\prime }x)\}\)

$$\frac{dS(y|x)}{dx_{j}}=S(y|x)log \{S(y|x)\}b_{j}$$

where \(\frac{dQ(t|x)}{dx_{j}}\) can be estimated by \(\frac{\Delta (t)}{\Delta (S)} (1-t)\) where $S$ and $t$ denote the surv and time components of the survfit object. Note that since \(t=1-S(y|x)\), the above is the value corresponding to the argument $(1-t)$; and furthermore

$$\frac{dt}{dx_{j}}=-\frac{dS(y|x)}{dx_{j}}=-(1-t) log (1-t)b_{j}$$

Thus the QTE at the mean of x's is:

$$(1-S)= \frac{\Delta (t)}{\Delta (S)}S ~log (S)b_{j}$$

Since \(\Delta S\) is negative and $log (S)$ is also negative this has the same sign as \(b_{j}\) The crq model fits the usual AFT form Surv(log(Time),Status), then

$$\frac{d log (Q(t|x))}{dx_{j}}=\frac{dQ(t|x)}{dx_{j}}/ Q(t|x)$$

This is the matrix form returned.

References

Koenker, R. and Geling, O. (2001). Reappraising Medfly longevity: a quantile regression survival analysis, J. Amer. Statist. Assoc., 96, 458-468

See Also

crq