calc_Wncdf {success} | R Documentation |
Calculate cdf of singletons W_n for CUSUM
Description
Internal function to calculate cdf of singletons W_n
of the Bernoulli CUSUM chart. The cdf is used to create the transition matrix
when Markov Chain methodology is used or to determine the integral equation/probabilities
of a Wald test when integral equation or Kemp's methodology is used.
Usage
calc_Wncdf(glmmod, theta, theta_true, p0, smooth_prob = FALSE)
Arguments
glmmod |
Generalized linear regression model used for risk-adjustment as produced by
the function glm() . Suggested:
glm(as.formula("(survtime <= followup) & (censorid == 1) ~ covariates"), data = data) .
Alternatively, a list containing the following elements:
formula :a formula() in the form ~ covariates ;
coefficients :a named vector specifying risk adjustment coefficients
for covariates. Names must be the same as in formula and colnames of data .
|
theta |
The \theta value used to specify the odds ratio
e^\theta under the alternative hypothesis.
If \theta >= 0 , the average run length for the upper one-sided
Bernoulli CUSUM will be determined. If \theta < 0 ,
the average run length for the lower one-sided CUSUM will be determined.
Note that
p_1 = \frac{p_0 e^\theta}{1-p_0 +p_0 e^\theta}.
|
theta_true |
The true log odds ratio \theta , describing the
true increase in failure rate from the null-hypothesis. Default = log(1), indicating
no increase in failure rate.
|
p0 |
The baseline failure probability at entrytime + followup for individuals.
|
smooth_prob |
Should the probability distribution of failure under the null distribution be smoothed?
Useful for small samples. Can only be TRUE when glmmod is supplied. Default = FALSE.
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[Package
success version 1.1.0
Index]