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Set up individual patient data (IPD)

Source: R/data_setup.R
set_ipd.Rd

Prepare IPD from the index treatment for an unanchored indirect comparison.

Usage

set_ipd(
  data,
  treatment,
  outcome = NULL,
  covariates,
  family = c("binomial", "normal", "poisson", "survival"),
  exposure = NULL,
  study = NULL,
  Surv = NULL,
  time = NULL,
  status = NULL,
  entry_time = NULL
)

Arguments

data

Data frame containing IPD

treatment

Column name for treatment variable

outcome

Column name for outcome variable. For family = "binomial", must be binary (0/1). For family = "normal", any numeric. For family = "poisson", non-negative integer counts. Not used (leave NULL) for family = "survival", which uses Surv/time/status instead.

covariates

Character vector of covariate column names

family

Outcome family: "binomial", "normal", "poisson", or "survival" (time-to-event)

exposure

Column name for exposure/time-at-risk (required when family = "poisson")

study

Column name for study identifier (optional)

Surv

For family = "survival", an optional survival::Surv() object describing the outcome (use for left/interval censoring or delayed entry).

time, status, entry_time

For family = "survival", character column names as an alternative to Surv (right-censoring with status 0/1, plus optional delayed entry).

Value

An object of class mlumr_ipd. Its $data holds the treatment, study, outcome and covariate columns under internal names, which cannot be used as column names in data.

Examples

if (FALSE) { # \dontrun{
# Binary outcome
ipd <- set_ipd(
  data = trial_a,
  treatment = "trt",
  outcome = "response",
  covariates = c("age", "sex")
)

# Continuous outcome
ipd <- set_ipd(
  data = trial_a,
  treatment = "trt",
  outcome = "score",
  covariates = c("age", "sex"),
  family = "normal"
)

# Count outcome with exposure
ipd <- set_ipd(
  data = trial_a,
  treatment = "trt",
  outcome = "events",
  covariates = c("age", "sex"),
  family = "poisson",
  exposure = "person_years"
)
} # }