Combine LMTP Models from Multiple Batches and Compute Cross-Batch Contrasts

This function merges LMTP models from multiple batch runs and computes user-specified contrasts across batches. This enables comparisons between shifts that were estimated in separate runs (e.g., comparing shift_zero from batch 2 with ipsi_02 from batch 1).

Usage

margot_lmtp_combine_and_contrast(
  ...,
  contrasts = NULL,
  contrast_scale = c("additive", "rr", "or"),
  auto_pairwise = FALSE,
  include_null_contrasts = TRUE,
  quiet = FALSE
)

Arguments

...

One or more LMTP output objects from margot_lmtp()

contrasts

Optional list of character vectors (each length 2) specifying contrast pairs. Example: list(c("shift_zero", "ipsi_02"), c("ipsi_10", "ipsi_05"))

contrast_scale

Scale for contrasts: "additive", "rr", or "or". Default is "additive".

auto_pairwise

Logical, if TRUE compute all pairwise contrasts among available shifts. Default is FALSE. If both contrasts and auto_pairwise are specified, contrasts takes precedence.

include_null_contrasts

Logical, if TRUE include contrasts against null shift when auto_pairwise = TRUE. Default is TRUE. Ignored when auto_pairwise = FALSE.

quiet

Logical, if TRUE suppress informational CLI messages. Default is FALSE.

Value

A list with the standard LMTP output structure:

models

NULL (not retained per design)

contrasts

List of contrasts by outcome

individual_tables

List of evaluation tables by outcome

combined_tables

List of combined tables across outcomes

Details

The function merges models by outcome and shift, then computes specified contrasts only where both shifts exist for the same outcome. Original models are not retained in the output. If an outcome is missing from one batch or a shift doesn't exist for a particular outcome, the function warns but continues processing valid contrasts.

Examples

if (FALSE) { # \dontrun{
# Run two separate LMTP batches with non-overlapping shifts
fit_batch_1 <- margot_lmtp(
  data = df,
  outcome_vars = c("outcome1", "outcome2"),
  trt = A,
  shift_functions = list(ipsi_02 = ipsi(2), ipsi_05 = ipsi(5)),
  include_null_shift = TRUE
)

fit_batch_2 <- margot_lmtp(
  data = df,
  outcome_vars = c("outcome1", "outcome2"),
  trt = A,
  shift_functions = list(ipsi_10 = ipsi(10), shift_zero = treatment_zero),
  include_null_shift = TRUE
)

# Combine and compute cross-batch contrasts
combined <- margot_lmtp_combine_and_contrast(
  fit_batch_1,
  fit_batch_2,
  contrasts = list(
    c("shift_zero", "ipsi_02"),
    c("shift_zero", "ipsi_05"),
    c("ipsi_10", "ipsi_02")
  ),
  contrast_scale = "additive"
)

# Or use automatic pairwise contrasts
combined_auto <- margot_lmtp_combine_and_contrast(
  fit_batch_1,
  fit_batch_2,
  auto_pairwise = TRUE,
  include_null_contrasts = TRUE,
  contrast_scale = "additive"
)
} # }