Calculate the survivor functions estimated in a 2nd order fractional polynomial NMA model. The absolute S(t) estimates combining the estimated baseline survival from a reference trial (in the NMA) with the fractional polynomial (log)hazard ratio estimates to construct the S(t) functions for each treatment.

Calculate the survivor functions estimated in a 2nd order fractional polynomial NMA model. The absolute S(t) estimates combining the estimated baseline survival from a reference trial (in the NMA) with the fractional polynomial (log)hazard ratio estimates to construct the S(t) functions for each treatment.

get_fp_2o_S(
  fit,
  ref.std,
  ref.arm,
  treatments,
  time = 1:24,
  bl.node = "mu",
  contrast.node = "d"
)

Arguments

fit

JAGS object with FP NMA fit.

ref.std

Numeric identifier of reference study to use for baseline survival estimate.

ref.arm

Numeric identifier of arm in reference study to use for baseline survival estimate.

treatments

Vector with character strings to label the treatments.

time

Vector of time-points at which S(t) functions are calculated.

bl.node

Charactor to identify the node in the jags model that identifies the baseline estimates (default is "mu").

contrast.node

Charactor to identify the node in the jags model that identifies the baseline estimates (default is "d").

Value

a data.frame containing survivor function for each treatment

Details

The FP parameters to calculate the log-hazard curves for each survivor function are combinations bl.node + contrast.node. This means the combination ref.std, ref.arm must identify a study arm in the NMA that used the (NMA) reference treatment. The basic parameters (contrasts vs reference) are then added to optain the parameters for each treatment in the study.

Examples