ICSKAT_fit_null_PO {ICSKAT}

ICSKAT_fit_null_PO.R

Description

Fit the null model (cubic basis spline for baseline cumulative hazard and coefficients for non-genetic coefficients) for interval-censored skat with PO model.

Usage

ICSKAT_fit_null_PO(
  init_beta,
  left_dmat,
  right_dmat,
  obs_ind,
  tpos_ind,
  lt,
  rt,
  checkpoint = FALSE,
  eps = 10^(-6)
)

Arguments

init_beta

(p+nknots+2)*1 vector of coefficients to initialize the Newton-Raphson.

left_dmat

n*(p+nknots+2) design matrix for left end of interval.

right_dmat

n*(p+nknots+2) design matrix for right end of interval.

obs_ind

n*1 vector of whether the event was observed before last follow-up.

tpos_ind

n*1 vector of whether the event was observed after follow-up started (t>0).

lt

n*1 vector of left side of interval times.

rt

n*1 vector of right side of interval times.

checkpoint

Boolean tells the function to print when each iteration completes.

eps

Stop when the L2 norm of the difference in model coefficients reaches this limit.

Value

A list with the elements:

beta_fit

(p+nknots+2)*1 vector of fitted coefficients under null model.

iter

Number of iterations needed to converge.

Itt

Fisher information matrix for the fitted coefficients.

diff_beta

Difference between beta_fit and previous iteration of the vector, can be checked for errors.

err

err=1 if NA shows up in the calculation.

IterrMsg

Describes the error.

Examples

set.seed(2)
xMat <- matrix(data=rnorm(200), nrow=100)
bhFunInv <- function(x) {x}
obsTimes <- 1:5
etaVec <- rep(0, 100)
outcomeDat <- gen_IC_data(bhFunInv = bhFunInv, obsTimes = obsTimes, windowHalf = 0.1,
probMiss = 0.1, etaVec = etaVec)
lt <- outcomeDat$leftTimes
rt <- outcomeDat$rightTimes
tpos_ind <- as.numeric(lt > 0)
obs_ind <- as.numeric(rt != Inf)
dmats <- make_IC_dmat(xMat = xMat, lt = lt, rt = rt, obs_ind = obs_ind,
tpos_ind = tpos_ind)
ICSKAT_fit_null_PO(init_beta = rep(0.1, 5), left_dmat = dmats$left_dmat,
right_dmat=dmats$right_dmat, obs_ind = obs_ind, tpos_ind = tpos_ind, lt = lt, rt = rt)