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The episode data behind a model

Source: R/episodes.R
tda_episodes.Rd

tda_episodes returns the episode data edef builds from a formula, which is what every model in this package is actually fitted to. It is the way to check that a Surv() specification means what you intended before trusting a fit.

Usage

tda_episodes(
  formula,
  data,
  vars = NULL,
  options = list(),
  dir = tempfile("tda"),
  ...
)

tda_state_dist(
  formula,
  data,
  times,
  id = NULL,
  spell = NULL,
  options = list(),
  dir = tempfile("tda"),
  ...
)

Arguments

formula

the same Surv() formula the model functions take.

data

a data frame.

vars

additional variables to carry into the output, as names.

options

a named list of further TDA options, passed through.

dir

working directory.

...

passed to tda_run.

times

time points at which to evaluate the state distribution.

id, spell

for tda_state_dist, columns identifying the case and numbering its spells, for multi-episode data (edef's id= and sn=).

Value

A data frame of episodes, or of state proportions by time.

Details

tda_state_dist gives the distribution over states at a set of time points – how many cases occupy each state when – which is the natural summary of multi-state data.

See also

Other episodes: tda_esort()

Examples

d <- data.frame(t = c(4, 3, 1, 5), s = c(1, 0, 1, 1), x = c(2, 1, 3, 1))
tda_episodes(Surv(t, s) ~ x, d)
#>   episode case subsample transition org des ts tf x
#> 1       1    1         1          1   0   1  0  4 2
#> 2       2    1         1          1   0   0  0  3 1
#> 3       3    1         1          1   0   1  0  1 3
#> 4       4    1         1          1   0   1  0  5 1
tda_state_dist(Surv(t, s) ~ x, d, times = c(1, 3, 5))
#>   time state1 total missing
#> 1    1      3     3       1
#> 2    3      2     2       2
#> 3    5      0     0       4