create_arm_lachin: Create a 'lachin' object

In npsurvSS: Sample Size and Power Calculation for Common Non-Parametric Tests in Survival Analysis

Create a 'lachin' object

Description

Create an object of class 'lachin' by specifying the trial parameters for a single arm, including the sample size, accrual distribution, survival distribution, loss to follow-up distribution, and study duration. 'Lachin' objects are also 'arm' objects, but with accrual limited to the uniform and truncated exponential distributions, and survival and loss to follow-up limited to the exponential distribution. 'Lachin' objects have the advantage that expectations for certain counting processes have closed form equations and can therefore be calculated more efficiently (Lachin and Foulkes, 1986).

Usage

create_arm_lachin(
  size,
  accr_time,
  accr_dist = "pieceuni",
  accr_param = NA,
  surv_median = NA,
  surv_exphazard = NA,
  surv_milestone = NA,
  loss_median = NA,
  loss_exphazard = NA,
  loss_milestone = NA,
  follow_time = Inf,
  total_time = Inf
)

Arguments

size	sample size. If total sample size is unknown, provide the integer sample size relative to the opposing arm, e.g. 1 for 1:2 randomization ratio or 2 for 2:3.
accr_time	accrual duration.
accr_dist	accrual distribution. Default is uniform (piecewise uniform with one interval). Alternatively, 'truncexp' allows for a truncated exponential distribution as proposed by Lachin and Foulkes (1986). Depending on the value of accr_param, this distribution can be either convex or concave.
accr_param	additional accrual parameter for accr_dist='truncexp'. accr_param>0 specifies a convex distribution and accr_param<0 specifies a concave distribution.
surv_median	median survival.
surv_exphazard	exponential hazard rate for the survival distribution.
surv_milestone	a tuple c(milestone, probability) that uniquely defines the exponential survival distribution, e.g. c(12, 0.8) corresponds to the exponential distribution with 80% survival rate at 12 months.
loss_median	median loss to follow-up.
loss_exphazard	exponential hazard rate for the loss to follow-up distribution.
loss_milestone	a tuple c(milestone, probability) that uniquely defines the exponential loss to follow-up distribution, e.g. c(12, 0.99) corresponds to the exponential distribution with 1% loss to follow-up at 12 months.
follow_time	Follow-up duration. Either follow_time or total_time (below) should be specified.
total_time	Total study duration. Either follow_time (above) or total_time should be specified.

Value

a list containing assumptions of size, accrual, censoring, survival, and follow-up for a single arm.

References

Lachin, J. M. and Foulkes, M. A. (1986) Evaluation of sample size and power for analyses of survival with allowance for nonuniform patient entry, losses to follow-up, noncompliance, and stratification. Biometrics, 42, 507-519.

See Also

create_arm for creating an object of class 'arm'.

Examples

# 3 arms with similar survival and loss to follow-up
create_arm_lachin(size=120, accr_time=6,
  surv_median=14,
  loss_median=140,
  follow_time=12)
create_arm_lachin(size=120, accr_time=6,
  surv_exphazard=0.05,
  loss_exphazard=0.005,
  follow_time=12)
create_arm_lachin(size=120, accr_time=6,
  accr_dist="truncexp",
  accr_param=0.1,
  surv_milestone=c(14, 0.5),
  loss_milestone=c(140, 0.5),
  total_time=18)

npsurvSS documentation built on May 29, 2024, 11:23 a.m.