CP (version 1.8)

ConPwrNonMixWei: Conditional Power (Non-Mixture-Weibull)

Description

Calculates the conditional power within the non-mixture model with Weibull type survival.

Usage

ConPwrNonMixWei(data, cont.time, new.pat = c(0, 0),
                 theta.0 = 1, alpha = 0.05,
                 disp.data = FALSE, plot.km = FALSE)

Value

See Details.

Returns a list which consists of the following components:

lambda1.hat

estimated scale parameter of group 1

k1.hat

estimated shape parameter of group 1

c1.hat

estimated survival fraction of group 1

lambda2.hat

estimated scale parameter of group 2

k2.hat

estimated shape parameter of group 2

c2.hat

estimated survival fraction of group 2

theta.hat

estimated hazard ratio = \(log(\)estimated survival fraction of group 2\()\) / \(log(\)estimated survival fraction of group 1\()\)

gamma.theta.0

conditional power

Arguments

data

Data frame which consists of at least three columns with the group (two different expressions) in the first, status (1 = event, 0 = censored) in the second and event time in the third column.

cont.time

Period of time of continuing the trial.

new.pat

2-dimensional vector which consists of numbers of new patients who will be recruited each time unit (first component = group 1, second component = group 2) with default at (0, 0).

theta.0

Originally postulated clinically relevant difference (hazard ratio = hazard of group 2 / hazard of group 1) with default at 1.

alpha

Significance level for conditional power calculations with default at 0.05.

disp.data

Logical value indicating if all calculated data should be displayed with default at FALSE.

plot.km

Logical value indicating if Kaplan-Meier curves and estimated survival curves according to the non-mixture model with Weibull type survival should be plotted with default at FALSE.

Author

Andreas Kuehnapfel

Details

This function calculates the conditional power within the non-mixture model with Weibull type survival, i. e. $$S(t) = c^(1 - e^(- \lambda t^k))$$ for all \(t \ge 0\), \(\lambda > 0\), \(k > 0\) and \(0 < c < 1\), and plots the conditional power curve.

Optionally, further data will be displayed. This includes data from interim analysis, log-likelihoods, AICs, calculated estimators and further patient times.

Moreover, it is possible to plot the Kaplan-Meier curves and the estimated survival curves according to the non-mixture model with Weibull type survival.

References

Kuehnapfel, A. (2013). Die bedingte Power in der Ueberlebenszeitanalyse.

See Also

CP
GenerateDataFrame
test

Examples

 # data frame 'test' generated by 'GenerateDataFrame'
 
 # conditional power calculations
 # within the non-mixture model with Weibull type survival
 ConPwrNonMixWei(data = test, cont.time = 12, new.pat = c(2.5, 2.5),
                 theta.0 = 0.75, alpha = 0.05,
                 disp.data = TRUE, plot.km = TRUE)