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Uses the stratified sample size formula from McCormick & Quist (2017) to determine how many sampling days are needed to achieve a target coefficient of variation on the effort estimate, given pilot variance estimates per day-type stratum.

Usage

creel_n_effort(cv_target, N_h, ybar_h, s2_h)

Arguments

cv_target

Numeric scalar. Target coefficient of variation for the effort estimate (e.g., 0.20 for 20 percent). Must be in (0, 1].

N_h

Named numeric vector. Total available days per stratum (e.g., c(weekday = 65, weekend = 28)). Values must be >= 1.

ybar_h

Numeric vector of same length as N_h. Pilot mean effort per day per stratum (e.g., angler-hours per day). Values must be >= 0.

s2_h

Numeric vector of same length as N_h. Pilot variance of effort per day per stratum. Values must be >= 0.

Value

A named integer vector. Elements named after strata in N_h give the sampling days required per stratum; element "total" gives the overall sample size before proportional allocation.

Details

Implements Cochran (1977) equation 5.25 under proportional allocation, as applied to creel surveys by McCormick & Quist (2017). The finite-population correction (FPC) factor is intentionally omitted (standard practice for pre-season planning where the goal is to determine how many days to sample, not to assess precision of a completed survey).

The per-stratum sample sizes n_h are computed from the total n_total under proportional allocation: n_h = ceiling(n_total * N_h / sum(N_h)). Because each stratum is ceiling-ed independently, sum(n_h) may exceed n_total.

References

McCormick, J.L. and Quist, M.C. 2017. Sample size estimation for on-site creel surveys. North American Journal of Fisheries Management 37:970-983. doi:10.1080/02755947.2017.1342723

Cochran, W.G. 1977. Sampling Techniques, 3rd ed. Wiley, New York.

See also

Examples

# Two-stratum weekday/weekend example
creel_n_effort(
  cv_target = 0.20,
  N_h = c(weekday = 65, weekend = 28),
  ybar_h = c(50, 60),
  s2_h = c(400, 500)
)
#> weekday weekend   total 
#>       3       2       4