TTEDesign class for target trial emulation

TTEDesign class for target trial emulation

TTEDesign class for target trial emulation

Details

Holds column name mappings that define the schema for trial data. This allows specifying variable names once and reusing them across all TTE workflow functions.

See also

[TTEEnrollment] for the trial class

Other tte_classes: TTEEnrollment, TTEPlan

Public fields

person_id_var

Character or NULL, person identifier column name.

id_var

Character, person-trial identifier column name.

exposure_var

Character, exposure/treatment column name.

outcome_vars

Character vector, outcome column names.

confounder_vars

Character vector, confounder column names.

follow_up_time

Integer, follow-up duration.

tstart_var

Character, period start time column name.

tstop_var

Character, period end time column name.

time_exposure_var

Character or NULL, time-varying exposure column.

eligible_var

Character or NULL, eligibility column name.

admin_censor_var

Character or NULL, admin censoring column.

admin_censor_isoyearweek

Character or NULL, admin censoring date.

period_width

Integer, band width in weeks for enrollment/aggregation.

Methods

Public methods

• TTEDesign$new()

• TTEDesign$check_version()

• TTEDesign$print()

• TTEDesign$clone()

---

Method new()

Create a new TTEDesign object.

Usage

TTEDesign$new(
  person_id_var = NULL,
  id_var = "enrollment_person_trial_id",
  exposure_var,
  outcome_vars,
  confounder_vars,
  follow_up_time,
  tstart_var = "tstart",
  tstop_var = "tstop",
  time_exposure_var = NULL,
  eligible_var = NULL,
  admin_censor_var = NULL,
  admin_censor_isoyearweek = NULL,
  period_width = 4L
)

Arguments

person_id_var

Character or NULL, name of the person identifier column for pre-panel (person-week) data (default: NULL).

id_var

Character, name of the person-trial identifier column (default: "enrollment_person_trial_id").

exposure_var

Character, name of the baseline exposure/treatment column.

outcome_vars

Character vector, names of outcome event indicator columns.

confounder_vars

Character vector, names of confounder columns for propensity/censoring models.

follow_up_time

Integer, expected follow-up duration in time units.

tstart_var

Character, name of period start time column (default: "tstart").

tstop_var

Character, name of period end time column (default: "tstop").

time_exposure_var

Character or NULL, name of time-varying exposure column for per-protocol analysis (default: NULL).

eligible_var

Character or NULL, name of eligibility indicator column (default: NULL).

admin_censor_var

Character or NULL, name of administrative censoring boundary column (default: NULL). Mutually exclusive with `admin_censor_isoyearweek`.

admin_censor_isoyearweek

Character or NULL, the study end date in ISO year-week format (e.g., "2023-52"). When set, administrative censoring is computed internally as weeks from each trial's entry date to this global study end date. Requires an `isoyearweek` column in the data. Mutually exclusive with `admin_censor_var` (default: NULL).

period_width

Integer, band width in weeks for enrollment and time aggregation (default: 4L). Calendar time is grouped into bands of this width. Must be a positive integer.

---

Method check_version()

Check if this object's schema version matches the current class version. Warns if the object was saved with an older schema version.

Usage

TTEDesign$check_version()

Returns

`invisible(TRUE)` if versions match, `invisible(FALSE)` otherwise.

---

Method print()

Print the TTEDesign object.

Usage

TTEDesign$print(...)

---

Method clone()

The objects of this class are cloneable with this method.

Usage

TTEDesign$clone(deep = FALSE)

Arguments

deep

Whether to make a deep clone.

Examples

# Design for post-panel (trial-level) data
design <- TTEDesign$new(
  id_var = "enrollment_person_trial_id",
  exposure_var = "baseline_exposed",
  outcome_vars = c("death", "hosp"),
  confounder_vars = c("age", "education"),
  follow_up_time = 156L
)

# Design for pre-panel (person-week) data with full workflow
design_prepanel <- TTEDesign$new(
  person_id_var = "id",
  exposure_var = "baseline_exposed",
  outcome_vars = c("death", "hosp"),
  confounder_vars = c("age", "education"),
  follow_up_time = 156L,
  eligible_var = "eligible"
)