snapshot.md
In weightflow: Declarative API for Staged Survey Weights

print() output is stable

Code
  print(snap_rec())
Output

  == Weighting specification (weightflow) ==
  Data    : 467 cases
  Base wts: pw
  Steps   :
    1. nonresponse (weighting class)
    2. calibration (raking)
  Status  : estimated (prep)

  Stage summary:
                      stage n_active sum_wts cv_wts deff_kish n_eff
                       base      467    4371  0.236     1.056   442
   stage_1_step_nonresponse      270    4371  0.172     1.029   262
     stage_2_step_calibrate      270    4495  0.232     1.054   256

  deff_kish = 1 + CV^2 (Kish design effect from unequal weighting);
  n_eff = n_active / deff_kish. Both worsen with each adjustment and
  improve with trimming.

summary() output (incl. the R-indicator line) is stable

Code
  summary(snap_rec())
Output

  == Weighting specification (weightflow) ==
  Data    : 467 cases
  Base wts: pw
  Steps   :
    1. nonresponse (weighting class)
    2. calibration (raking)
  Status  : estimated (prep)

  Stage summary:
                      stage n_active sum_wts cv_wts deff_kish n_eff
                       base      467    4371  0.236     1.056   442
   stage_1_step_nonresponse      270    4371  0.172     1.029   262
     stage_2_step_calibrate      270    4495  0.232     1.054   256

  deff_kish = 1 + CV^2 (Kish design effect from unequal weighting);
  n_eff = n_active / deff_kish. Both worsen with each adjustment and
  improve with trimming.

  --- Step 1: nonresponse (weighting class) ---
        cell n_respondents n_nonresponse   factor
    East | F            33            18 1.545455
    East | M            19            26 2.368421
   North | F            38            20 1.526316
   North | M            40            21 1.525000
   South | F            35            26 1.742857
   South | M            37            23 1.621622
    West | F            24            25 2.041667
    West | M            44            38 1.863636
  Kish deff: 1.056 -> 1.029   |   n_eff: 442 -> 262

  --- Step 2: calibration (raking) ---
   variable category target achieved
     region    North   1570     1570
     region    South   1250     1250
     region     East    927      927
     region     West    748      748
        sex        F   2311     2311
        sex        M   2184     2184
  (converged/iterated in 5 iterations)
  Kish deff: 1.029 -> 1.054   |   n_eff: 262 -> 256

  R-indicator (representativity of response): 0.890  (on region, sex)

design_effect() output is stable

Code
  str(design_effect(collect_weights(snap_rec())$.weight))
Output
  List of 4
   $ deff : num 1.05
   $ n_eff: num 256
   $ cv   : num 0.232
   $ n    : int 270