Compare multiple survey design estimates side by side

Usage

compare_designs(designs, metric = "estimate")

Arguments

designs

Named list of creel_estimates objects. Names become the design column in the output. At least two elements are required.

metric

Character scalar. Which estimate column to compare. Default "estimate". Must be a column present in every estimates data frame.

Value

A creel_design_comparison object – a data frame with columns:

design

Design name (from names(designs)).

estimate

Point estimate.

se

Standard error.

rse

Relative standard error (se / |estimate|).

ci_lower

Lower confidence interval bound.

ci_upper

Upper confidence interval bound.

ci_width

Width of the confidence interval.

n

Sample size (if present in the estimates frame).

Group columns are retained when all designs share the same by-variable structure.

Details

Takes a named list of creel_estimates objects (from different survey designs or methods), extracts key precision metrics from each, and returns a tidy comparison tibble. An autoplot() method renders a forest plot of point estimates with confidence intervals.

See also

autoplot.creel_design_comparison()

Other "Planning & Sample Size": audit_strata(), creel_n_camera(), creel_n_cpue(), creel_n_effort(), creel_power(), cv_from_n(), optimal_n(), power_creel(), reallocate_strata(), simulate_strata_collapse()

Examples

data(example_calendar)
data(example_counts)
data(example_interviews)

design <- creel_design(example_calendar, date = date, strata = day_type)
design <- add_counts(design, example_counts)
#> Warning: No weights or probabilities supplied, assuming equal probability
design <- add_interviews(design, example_interviews,
  catch = catch_total, effort = hours_fished, harvest = catch_kept,
  trip_status = trip_status
)
#> Warning: ! No `n_anglers` provided — assuming 1 angler per interview.
#> ℹ Pass `n_anglers = <column>` to use actual party sizes for angler-hour
#>   normalization.
#> ℹ If the interviews really are one angler each, pass `n_anglers = 1` to state
#>   that and silence this warning.
#> ℹ Added 22 interviews: 17 complete (77%), 5 incomplete (23%)

# Two estimates from the same design: overall, and split by stratum. In
# practice these would come from designs built on different survey types.
est_all <- estimate_effort(design)
est_grp <- estimate_effort(design, by = day_type)

compare_designs(list(overall = est_all, by_day_type = est_grp))
#> 
#> ── Survey Design Comparison ────────────────────────────────────────────────────
#> 3 row(s), 2 design(s)
#> 
#>        design estimate    se    rse ci_lower ci_upper ci_width  n day_type
#> 1     overall      372 13.18 0.0354      344      401     57.4 14       NA
#> 2 by_day_type      171  9.67 0.0567      150      192     42.2 10  weekday
#> 3 by_day_type      202  8.95 0.0443      182      221     39.0  4  weekend