surveycore (version 0.8.3)

as_survey_twophase: Create a Two-Phase Survey Design

Description

Creates a two-phase (double) sampling design from an existing survey_taylor Phase 1 object. Phase 1 covers all rows; Phase 2 is a strict subset indicated by a logical column. Uses a tidy-select interface for all Phase 2 design variable arguments.

Usage

as_survey_twophase(
  phase1,
  ids2 = NULL,
  strata2 = NULL,
  probs2 = NULL,
  fpc2 = NULL,
  subset,
  method = c("full", "approx", "simple")
)

Value

A survey_twophase object.

Arguments

phase1

A survey design object (inheriting from survey_base) representing the Phase 1 design. Accepts survey_taylor or survey_replicate objects. Its @data must contain ALL rows from both phases, plus a logical indicator column for Phase 2 membership. Create with as_survey() or as_survey_replicate().

ids2

<tidy-select> Phase 2 cluster ID column(s). For single-stage Phase 2: ids2 = psu2. For multi-stage: ids2 = c(psu2, ssu2). Omit if Phase 2 has no within-stratum clustering.

strata2

<tidy-select> Phase 2 stratification column (a single column). Optional.

probs2

<tidy-select> Phase 2 inclusion probability column (a single column, values in (0, 1]). Optional.

fpc2

<tidy-select> Phase 2 finite population correction column (a single column). Optional.

subset

<tidy-select> Single logical column in phase1@data. TRUE = row selected into Phase 2; FALSE = Phase 1 only. Required. Must contain both TRUE and FALSE values (non-degenerate).

method

Character. Variance estimation method for combining Phase 1 and Phase 2 variability. One of "full" (default), "approx", or "simple". Case-sensitive. See Details.

Details

Variance methods

• "full" — Full two-phase variance formula. Accounts for variability in both phases. Requires Phase 2 design information (probs2, ids2, strata2) when Phase 2 is not a simple random subsample. If none of these are provided, a warning is issued and Phase 2 selection is treated as SRS within Phase 1 strata.

• "approx" — Approximation that ignores Phase 1 sampling variability. Faster but less accurate than "full" when the Phase 1 sampling fraction is non-negligible.

• "simple" — Treats Phase 2 as a single-phase design, ignoring Phase 1. Only valid when Phase 1 is a census (no sampling). Issues a warning when Phase 1 has PSU cluster variables, because this understates variance for clustered designs.

References

Sarndal, C-E., Swensson, B. and Wretman, J. (1992) Model Assisted Survey Sampling. Springer.

Breslow, N.E. and Chatterjee, N. (1999) Design and analysis of two-phase studies with binary outcome applied to Wilms tumour prognosis. Applied Statistics 48, 457--468.

Breslow, N., Lumley, T., Ballantyne, C.M., Chambless, L.E. and Kulick, M. (2009) Improved Horvitz-Thompson estimation of model parameters from two-phase stratified samples: applications in epidemiology. Statistics in Biosciences. tools:::Rd_expr_doi("10.1007/s12561-009-9001-6")

See Also

as_survey() for Taylor series designs, as_survey_replicate() for replicate-weight designs

Other constructors: as_survey(), as_survey_nonprob(), as_survey_replicate(), survey_data(), survey_glm(), survey_glm_fit(), survey_nonprob(), survey_replicate(), survey_taylor(), survey_twophase()

Examples

# Minimal two-phase design: Phase 1 = full cohort, Phase 2 = random subset
df <- data.frame(
  id        = 1:20,
  wt        = rep(2, 20),
  in_phase2 = c(rep(TRUE, 10), rep(FALSE, 10)),
  y         = rnorm(20)
)
phase1 <- as_survey(df, ids = id, weights = wt)
d2 <- as_survey_twophase(phase1, subset = in_phase2)

# With Phase 2 stratification and inclusion probabilities
df2 <- data.frame(
  id          = 1:30,
  wt          = rep(3, 30),
  in_phase2   = c(rep(TRUE, 15), rep(FALSE, 15)),
  arm         = rep(c("A", "B", "C"), 10),
  subsamprate = rep(c(0.5, 0.7, 0.3), 10),
  y           = rnorm(30)
)
phase1b <- as_survey(df2, ids = id, weights = wt)
d2b <- as_survey_twophase(
  phase1b,
  strata2 = arm,
  probs2  = subsamprate,
  subset  = in_phase2,
  method  = "full"
)