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Add functionality to grpsurv for start stop survival times #45

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02951af
add functionality to grpsurv for start stop survival times
jwallib Jul 13, 2021
d00eabe
add functionality for start stop survival times to rest of package
jwallib Jul 13, 2021
8fbeef1
Merge branch 'master' into master
jwallib Jul 14, 2021
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3 changes: 2 additions & 1 deletion DESCRIPTION
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Expand Up @@ -5,7 +5,8 @@ Date: 2021-07-13
Authors@R: c(
person("Patrick", "Breheny", role=c("aut","cre"), email="patrick-breheny@uiowa.edu", comment=c(ORCID="0000-0002-0650-1119")),
person("Yaohui", "Zeng", role="ctb"),
person("Ryan", "Kurth", role="ctb"))
person("Ryan", "Kurth", role="ctb"),
person("Jamie", "Wallis", role="ctb"))
Depends: R (>= 3.1.0)
Imports: Matrix
Suggests: knitr, rmarkdown, splines, survival, tinytest
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2 changes: 1 addition & 1 deletion R/auc.R
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Expand Up @@ -4,7 +4,7 @@ AUC.cv.grpsurv <- function(obj, ...) {
stop("The 'survival' package is needed for AUC() to work. Please install it.", call. = FALSE)
}
if (packageVersion("survival") < "3.2.10") stop("AUC.cv.ncvsurv requires version 3.2.10 of 'survival' package or higher", call.=FALSE)
S <- survival::Surv(obj$fit$time, obj$fit$fail)
S <- survival::Surv(obj$fit$start_time, obj$fit$stop_time, obj$fit$fail)
res <- apply(obj$Y, 2, concord, y = S)
num <- res['concordant',] + 0.5*res['tied.x',] + 0.5*res['tied.y',] + 0.5*res['tied.xy',]
num/sum(res[,1])
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2 changes: 1 addition & 1 deletion R/cv-grpsurv.R
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Expand Up @@ -11,7 +11,7 @@ cv.grpsurv <- function(X, y, group, ..., nfolds=10, seed, fold, se=c('quick', 'b

# Get standardized X, y
X <- fit$XG$X
y <- cbind(fit$time, fit$fail)
y <- cbind(fit$start_time, fit$stop_time, fit$fail)
returnX <- list(...)$returnX
if (is.null(returnX) || !returnX) fit$X <- NULL

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12 changes: 7 additions & 5 deletions R/grpsurv.R
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Expand Up @@ -42,24 +42,25 @@ grpsurv <- function(X, y, group=1:ncol(X), penalty=c("grLasso", "grMCP", "grSCAD

# Set up lambda
if (missing(lambda)) {
lambda <- setupLambdaCox(XG$X, Y$time, Y$fail, XG$g, penalty, alpha, lambda.min, nlambda, XG$m)
lambda <- setupLambdaCox(XG$X, Y, XG$g, penalty, alpha, lambda.min, nlambda, XG$m)
user.lambda <- FALSE
} else {
nlambda <- length(lambda)
user.lambda <- TRUE
}

## Fit
n <- length(Y$time)
n <- length(Y$fail)
p <- ncol(XG$X)
K <- as.integer(table(XG$g))
K0 <- as.integer(if (min(XG$g)==0) K[1] else 0)
K1 <- as.integer(if (min(XG$g)==0) cumsum(K) else c(0, cumsum(K)))
start_order = as.numeric(order(Y$start_time))
if (bilevel) {
res <- .Call("lcdfit_cox", XG$X, Y$fail, penalty, K1, K0, lambda, alpha, eps, 0, gamma, tau, as.integer(max.iter),
res <- .Call("lcdfit_cox", XG$X, Y$start_time, start_order, Y$stop_time, Y$fail, penalty, K1, K0, lambda, alpha, eps, 0, gamma, tau, as.integer(max.iter),
XG$m, as.integer(dfmax), as.integer(gmax), as.integer(warn), as.integer(user.lambda))
} else {
res <- .Call("gdfit_cox", XG$X, Y$fail, penalty, K1, K0, lambda, alpha, eps, as.integer(max.iter),
res <- .Call("gdfit_cox", XG$X, Y$start_time, start_order, Y$stop_time, Y$fail, penalty, K1, K0, lambda, alpha, eps, as.integer(max.iter),
as.double(gamma), XG$m, as.integer(dfmax), as.integer(gmax), as.integer(warn), as.integer(user.lambda))
}
b <- matrix(res[[1]], p, nlambda)
Expand Down Expand Up @@ -101,7 +102,8 @@ grpsurv <- function(X, y, group=1:ncol(X), penalty=c("grLasso", "grMCP", "grSCAD
df = df,
iter = iter,
group.multiplier = XG$m,
time = Y$time,
start_time = Y$start_time,
stop_time = Y$stop_time,
fail = Y$fail,
order = Y$ind,
linear.predictors = sweep(Eta, 2, colMeans(Eta), '-')),
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18 changes: 16 additions & 2 deletions R/loss.R
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Expand Up @@ -22,15 +22,29 @@ loss.grpreg <- function(y, yhat, family) {
val
}
loss.grpsurv <- function(y, eta, total=TRUE) {
ind <- order(y[,1])
d <- as.integer(y[ind,2])
ind <- order(y[,2])
d <- as.integer(y[ind,3])
if (is.matrix(eta)) {
eta <- eta[ind, , drop=FALSE]
r <- apply(eta, 2, function(x) rev(cumsum(rev(exp(x)))))
} else {
eta <- as.matrix(eta[ind])
r <- as.matrix(rev(cumsum(rev(exp(eta)))))
}
n = nrow(y)
current_sum = 0
start_idx = n
stop_idx = n
start_o = order(y[,1])
while(start_idx>0 && stop_idx >0){
if(y[start_o[start_idx],1]<y[ind[stop_idx],2]){
r[stop_idx,] = r[stop_idx,] - current_sum
stop_idx = stop_idx - 1
}else{
current_sum = current_sum + exp(eta[start_o[start_idx],])
start_idx = start_idx - 1
}
}
if (total) {
return(-2*(crossprod(d, eta) - crossprod(d, log(r))))
} else {
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19 changes: 15 additions & 4 deletions R/newS.R
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@@ -1,6 +1,17 @@
newS <- function(y) {
ind <- order(y[,1])
list(time = as.double(y[ind,1]),
fail = as.double(y[ind,2]),
ind = ind)
if(ncol(y) == 2){
ind <- order(y[,1])
list(start_time = as.double(rep(0,nrow(y))),
stop_time = as.double(y[ind,1]),
fail = as.double(y[ind,2]),
ind = ind)
}else if(ncol(y)==3){
ind <- order(y[,2])
list(start_time = as.double(y[ind,1]),
stop_time = as.double(y[ind,2]),
fail = as.double(y[ind,3]),
ind = ind)
}else{
stop('y must be specified as Surv(time,fail) or Surv(start,stop,fail)')
}
}
4 changes: 2 additions & 2 deletions R/predict-surv.R
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Expand Up @@ -97,7 +97,7 @@ predict.grpsurv <- function(object, X,
a <- ifelse(object$fail, (1-w/r)^(1/w), 1)
S0 <- c(1, cumprod(a))
H0 <- c(0, cumsum(1-a))
x <- c(0, object$time)
x <- c(0, object$stop_time)
for (i in 1:nrow(eta)) {
S <- S0^exp(eta[i,j])
H <- H0*exp(eta[i,j])
Expand All @@ -113,7 +113,7 @@ predict.grpsurv <- function(object, X,
if (type %in% c('survival', 'hazard')) {
if (nrow(eta)==1) val <- val[[1]]
class(val) <- c('grpsurv.func', class(val))
attr(val, 'time') <- object$time
attr(val, 'time') <- object$stop_time
} else if (type == 'median') {
val <- drop(val)
}
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2 changes: 1 addition & 1 deletion R/residuals.R
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Expand Up @@ -23,7 +23,7 @@ residuals.grpreg <- function(object, lambda, which=1:length(object$lambda), drop
# Calculate matrix of residuals
if (inherits(object, 'grpsurv')) {
for (j in 1:length(object$lambda)) {
h <- suppressWarnings(predict(object, which=j, type='hazard')(object$time))
h <- suppressWarnings(predict(object, which=j, type='hazard')(object$stop_time))
M <- object$fail - h * exp(object$linear.predictors)
R <- sign(M) * sqrt(-2*(M + object$fail*log(object$fail-M)))
R[h==0,] <- 0
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21 changes: 17 additions & 4 deletions R/setupLambdaCox.R
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@@ -1,4 +1,4 @@
setupLambdaCox <- function(X, y, Delta, group, penalty, alpha, lambda.min, nlambda, group.multiplier) {
setupLambdaCox <- function(X, y, group, penalty, alpha, lambda.min, nlambda, group.multiplier) {
n <- nrow(X)
p <- ncol(X)

Expand All @@ -8,13 +8,26 @@ setupLambdaCox <- function(X, y, Delta, group, penalty, alpha, lambda.min, nlamb
if (K1[1]!=0) {
SURV <- get("Surv", asNamespace("survival"))
COXPH <- get("coxph", asNamespace("survival"))
nullFit <- COXPH(SURV(y, Delta) ~ X[, group==0, drop=FALSE])
nullFit <- COXPH(SURV(y$start_time, y$stop_time, y$fail) ~ X[, group==0, drop=FALSE])
eta <- nullFit$linear.predictors
rsk <- rev(cumsum(rev(exp(eta))))
s <- Delta - exp(eta)*cumsum(Delta/rsk)
current_sum = 0
start_idx = n
stop_idx = n
start_o = order(y[,1])
while(start_idx>0 && stop_idx >0){
if(y[start_o[start_idx],1]<y[ind[stop_idx],2]){
rsk[stop_idx] = rsk[stop_idx] - current_sum
stop_idx = stop_idx - 1
}else{
current_sum = current_sum + exp(eta[start_o[start_idx]])
start_idx = start_idx - 1
}
}
s <- y$fail - exp(eta)*cumsum(y$fail/rsk)
} else {
w <- 1/(n-(1:n)+1)
s <- Delta - cumsum(Delta*w)
s <- y$fail - cumsum(y$fail*w)
}

## Determine lambda.max
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20 changes: 19 additions & 1 deletion src/gdfit_cox.c
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Expand Up @@ -45,7 +45,7 @@ void gd_cox(double *b, double *x, double *r, double *eta, double v, int g,
Free(z);
}

SEXP gdfit_cox(SEXP X_, SEXP d_, SEXP penalty_, SEXP K1_, SEXP K0_, SEXP lambda, SEXP alpha_, SEXP eps_, SEXP max_iter_, SEXP gamma_, SEXP group_multiplier, SEXP dfmax_, SEXP gmax_, SEXP warn_, SEXP user_) {
SEXP gdfit_cox(SEXP X_, SEXP start_, SEXP start_o_, SEXP stop_, SEXP d_, SEXP penalty_, SEXP K1_, SEXP K0_, SEXP lambda, SEXP alpha_, SEXP eps_, SEXP max_iter_, SEXP gamma_, SEXP group_multiplier, SEXP dfmax_, SEXP gmax_, SEXP warn_, SEXP user_) {

// Lengths/dimensions
int n = length(d_);
Expand All @@ -55,6 +55,9 @@ SEXP gdfit_cox(SEXP X_, SEXP d_, SEXP penalty_, SEXP K1_, SEXP K0_, SEXP lambda,

// Pointers
double *X = REAL(X_);
double *start_time = REAL(start_);
double *start_o = REAL(start_o_);
double *stop_time = REAL(stop_);
double *d = REAL(d_);
const char *penalty = CHAR(STRING_ELT(penalty_, 0));
int *K1 = INTEGER(K1_);
Expand Down Expand Up @@ -98,6 +101,8 @@ SEXP gdfit_cox(SEXP X_, SEXP d_, SEXP penalty_, SEXP K1_, SEXP K0_, SEXP lambda,
for (int g=0; g<J; g++) e[g] = 0;
int lstart, ng, nv, violations;
double shift, l1, l2, nullDev, v, s, maxChange;
double current_sum;
int start_idx, stop_idx, ss;

// Initialization
// If lam[0]=lam_max, skip lam[0] -- closed form sol'n available
Expand Down Expand Up @@ -147,6 +152,19 @@ SEXP gdfit_cox(SEXP X_, SEXP d_, SEXP penalty_, SEXP K1_, SEXP K0_, SEXP lambda,
for (int i=n-2; i>=0; i--) {
rsk[i] = rsk[i+1] + haz[i];
}
current_sum = 0;
start_idx = n;
stop_idx = n;
while(start_idx>0 && stop_idx>0){
ss = start_o[start_idx];
if(start_time[ss] < stop_time[stop_idx]){
rsk[stop_idx] = rsk[stop_idx] - current_sum;
stop_idx = stop_idx - 1;
}else{
current_sum = current_sum + haz[ss];
start_idx = start_idx - 1;
}
}
for (int i=0; i<n; i++) {
REAL(Loss)[l] += d[i]*eta[i] - d[i]*log(rsk[i]);
}
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8 changes: 4 additions & 4 deletions src/grpreg_init.c
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Expand Up @@ -7,21 +7,21 @@

/* .Call calls */
extern SEXP gdfit_glm(SEXP, SEXP, SEXP, SEXP, SEXP, SEXP, SEXP, SEXP, SEXP, SEXP, SEXP, SEXP, SEXP, SEXP, SEXP, SEXP);
extern SEXP gdfit_cox(SEXP, SEXP, SEXP, SEXP, SEXP, SEXP, SEXP, SEXP, SEXP, SEXP, SEXP, SEXP, SEXP, SEXP, SEXP);
extern SEXP gdfit_cox(SEXP, SEXP, SEXP, SEXP, SEXP, SEXP, SEXP, SEXP, SEXP, SEXP, SEXP, SEXP, SEXP, SEXP, SEXP, SEXP, SEXP, SEXP);
extern SEXP gdfit_gaussian(SEXP, SEXP, SEXP, SEXP, SEXP, SEXP, SEXP, SEXP, SEXP, SEXP, SEXP, SEXP, SEXP, SEXP, SEXP);
extern SEXP lcdfit_glm(SEXP, SEXP, SEXP, SEXP, SEXP, SEXP, SEXP, SEXP, SEXP, SEXP, SEXP, SEXP, SEXP, SEXP, SEXP, SEXP, SEXP, SEXP);
extern SEXP lcdfit_cox(SEXP, SEXP, SEXP, SEXP, SEXP, SEXP, SEXP, SEXP, SEXP, SEXP, SEXP, SEXP, SEXP, SEXP, SEXP, SEXP, SEXP);
extern SEXP lcdfit_cox(SEXP, SEXP, SEXP, SEXP, SEXP, SEXP, SEXP, SEXP, SEXP, SEXP, SEXP, SEXP, SEXP, SEXP, SEXP, SEXP, SEXP, SEXP, SEXP, SEXP);
extern SEXP lcdfit_gaussian(SEXP, SEXP, SEXP, SEXP, SEXP, SEXP, SEXP, SEXP, SEXP, SEXP, SEXP, SEXP, SEXP, SEXP, SEXP, SEXP);
extern SEXP maxgrad(SEXP, SEXP, SEXP, SEXP);
extern SEXP maxprod(SEXP, SEXP, SEXP, SEXP);
extern SEXP standardize(SEXP);

static const R_CallMethodDef CallEntries[] = {
{"gdfit_glm", (DL_FUNC) &gdfit_glm, 16},
{"gdfit_cox", (DL_FUNC) &gdfit_cox, 15},
{"gdfit_cox", (DL_FUNC) &gdfit_cox, 18},
{"gdfit_gaussian", (DL_FUNC) &gdfit_gaussian, 15},
{"lcdfit_glm", (DL_FUNC) &lcdfit_glm, 18},
{"lcdfit_cox", (DL_FUNC) &lcdfit_cox, 17},
{"lcdfit_cox", (DL_FUNC) &lcdfit_cox, 20},
{"lcdfit_gaussian", (DL_FUNC) &lcdfit_gaussian, 16},
{"maxgrad", (DL_FUNC) &maxgrad, 4},
{"maxprod", (DL_FUNC) &maxprod, 4},
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22 changes: 20 additions & 2 deletions src/lcdfit_cox.c
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Expand Up @@ -133,7 +133,7 @@ int gLCD_cCheck(double *b, const char *penalty, double *X, double *r, double *et
return(violations);
}

SEXP lcdfit_cox(SEXP X_, SEXP d_, SEXP penalty_, SEXP K1_, SEXP K0_,
SEXP lcdfit_cox(SEXP X_, SEXP start_, SEXP start_o_, SEXP stop_, SEXP d_, SEXP penalty_, SEXP K1_, SEXP K0_,
SEXP lambda, SEXP alpha_, SEXP eps_, SEXP delta_, SEXP gamma_,
SEXP tau_, SEXP max_iter_, SEXP group_multiplier, SEXP dfmax_,
SEXP gmax_, SEXP warn_, SEXP user_) {
Expand All @@ -146,6 +146,9 @@ SEXP lcdfit_cox(SEXP X_, SEXP d_, SEXP penalty_, SEXP K1_, SEXP K0_,

// Pointers
double *X = REAL(X_);
double *start_time = REAL(start_);
double *start_o = REAL(start_o_);
double *stop_time = REAL(stop_);
double *d = REAL(d_);
const char *penalty = CHAR(STRING_ELT(penalty_, 0));
int *K1 = INTEGER(K1_);
Expand Down Expand Up @@ -191,7 +194,9 @@ SEXP lcdfit_cox(SEXP X_, SEXP d_, SEXP penalty_, SEXP K1_, SEXP K0_,
for (int j=0; j<p; j++) e[j] = 0;
int lstart, ng, nv, violations;
double shift, l1, l2, nullDev, u, v, s, xwr, xwx, maxChange;

double current_sum;
int start_idx, stop_idx, ss;

// Initialization
rsk[n-1] = 1;
for (int i=n-2; i>=0; i--) rsk[i] = rsk[i+1] + 1;
Expand Down Expand Up @@ -256,6 +261,19 @@ SEXP lcdfit_cox(SEXP X_, SEXP d_, SEXP penalty_, SEXP K1_, SEXP K0_,
for (int i=n-2; i>=0; i--) {
rsk[i] = rsk[i+1] + haz[i];
}
current_sum = 0;
start_idx = n;
stop_idx = n;
while(start_idx>0 && stop_idx>0){
ss = start_o[start_idx];
if(start_time[ss] < stop_time[stop_idx]){
rsk[stop_idx] = rsk[stop_idx] - current_sum;
stop_idx = stop_idx - 1;
}else{
current_sum = current_sum + haz[ss];
start_idx = start_idx - 1;
}
}
for (int i=0; i<n; i++) {
REAL(Loss)[l] += d[i]*eta[i] - d[i]*log(rsk[i]);
}
Expand Down