View source: R/cgr_control_limit.R
cgr_control_limit | R Documentation |
This function can be used to determine control limits for the
CGR-CUSUM (cgr_cusum
) procedure by restricting the type I error alpha
of the
procedure over time
.
cgr_control_limit(time, alpha = 0.05, psi, n_sim = 20, coxphmod, cbaseh, inv_cbaseh, baseline_data, interval = c(0, 9e+12), h_precision = 0.01, ncores = 1, seed = 1041996, pb = FALSE, chartpb = FALSE)
time |
A numeric value over which the type I error |
alpha |
A proportion between 0 and 1 indicating the required maximal type I error. Default is 0.05. |
psi |
A numeric value indicating the estimated Poisson arrival rate of subjects
at their respective units. Can be determined using
|
n_sim |
An integer value indicating the amount of units to generate for the determination of the control limit. Larger values yield more precise control limits, but greatly increase computation times. Default is 20. |
coxphmod |
(optional): A cox proportional hazards regression model as
produced by
the function
|
cbaseh |
(optional): A function that returns the unadjusted cumulative
baseline hazard H_0(t). If |
inv_cbaseh |
(optional): A function that returns the unadjusted inverse cumulative
baseline
hazard H_0^-1(t). If |
baseline_data |
(optional): A
and optionally additional covariates used for risk-adjustment. Can only be specified
in combination with |
interval |
(optional): Interval in which survival times should be solved for numerically. |
h_precision |
(optional): A numerical value indicating how precisely the control limit should be determined. By default, control limits will be determined up to 2 significant digits. |
ncores |
(optional): Number of cores to use to parallelize the computation of the
CGR-CUSUM charts. If ncores = 1 (default), no parallelization is done. You
can use |
seed |
(optional): A numeric seed for survival time generation. Default = my birthday. |
pb |
(optional): A boolean indicating whether a progress bar should
be shown. Default is |
chartpb |
(optional): A boolean indicating whether progress bars should
be displayed for the constructions of the charts. Default is |
This function performs 3 steps to determine a suitable control limit.
Step 1: Generates n_sim
in-control units (failure rate as baseline).
If data
is provided, subject covariates are resampled from the data set.
Step 2: Determines chart values for all simulated units.
Step 3: Determines control limits such that at most a proportion alpha
of all units cross the control limit.
The generated data as well as the charts are also returned in the output.
A list containing three components:
call
: the call used to obtain output;
charts
: A list of length n_sim
containing the constructed charts;
data
: A data.frame
containing the in-control generated data.
h
: Determined value of the control limit.
Daniel Gomon
plot.cgrcusum
, runlength.cgrcusum
Other control limit simulation:
bernoulli_control_limit()
,
bk_control_limit()
require(survival) ## Not run: require(survival) exprfit <- as.formula("Surv(survtime, censorid) ~ age + sex + BMI") tcoxmod <- coxph(exprfit, data= surgerydat) a <- cgr_control_limit(time = 500, alpha = 0.1, cbaseh = function(t) chaz_exp(t, lambda = 0.02), inv_cbaseh = function(t) inv_chaz_exp(t, lambda = 0.02), psi = 0.5, n_sim = 10) b <- cgr_control_limit(time = 500, alpha = 0.1, coxphmod = tcoxmod, psi = 0.5, n_sim = 10, data = subset(surgerydat, hosp_num == 1)) ## End(Not run)
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