rctglm_prog_methods.md
In postcard: Estimating Marginal Effects with Prognostic Covariate Adjustment

`rctglm_with_prognosticscore` returns object of correct class

Code
  prog(ate)
Output
  $formula
  Y ~ .


  $model_fit
  == Workflow [trained] ==========================================================
  Preprocessor: Formula
  Model: mars()

  -- Preprocessor ----------------------------------------------------------------
  Y ~ .

  -- Model -----------------------------------------------------------------------
  Selected 3 of 12 terms, and 1 of 1 predictors
  Termination condition: Reached nk 21
  Importance: W1
  Number of terms at each degree of interaction: 1 2 (additive model)
  GCV 1.073623    RSS 94.86537    GRSq 0.2633666    RSq 0.3358951

  $learners
  $learners$mars
  $learners$mars$model
  MARS Model Specification (regression)

  Main Arguments:
    prod_degree = 3

  Computational engine: earth



  $learners$lm
  $learners$lm$model
  Linear Regression Model Specification (regression)

  Computational engine: lm




  $cv_folds
  [1] 5

  $data
                Y          W1
  1    0.49320997  1.65922417
  2    2.81020807  1.74830165
  3    3.30361633 -0.85544186
  4    4.51327610  1.32179050
  5    0.42877160  0.56698208
  6   -0.03639125  0.07638380
  7    1.51111188  0.94635326
  8    1.43696662 -1.46133361
  9    1.23551013  0.62796916
  10   1.91160592  0.82025914
  11   0.05112161 -0.16903290
  12   4.18967942  0.87644901
  13   2.58668340  1.73868899
  14   2.16020293 -0.97828470
  15   1.72100587 -0.15082871
  16   2.51063027  1.76005809
  17   2.28098564  1.91290571
  18   3.97554243 -1.53005055
  19   0.93273734 -0.10001167
  20   0.07489067  0.24133098
  21   2.88412710  1.61612555
  22   2.13666420 -1.44515933
  23   1.86853076  1.95556692
  24   1.39705230  1.78667293
  25   2.92095378 -1.67024977
  26   0.91120655  0.05684714
  27   2.15347219 -0.43918613
  28   2.26359498  1.62295252
  29   0.65729804 -0.21212149
  30   3.71183000  1.34401704
  31   1.94869317  0.95038247
  32   3.36867159  1.24422057
  33   0.44757758 -0.44756687
  34   1.54606758  0.74067892
  35   2.10428277 -1.98420664
  36   2.06635049  1.33166432
  37   3.73037613 -1.97066341
  38   2.35798878 -1.16936411
  39   2.74190715  1.62640563
  40   0.70617662  0.44711457
  41   0.96579612 -0.48176304
  42   2.37921399 -0.25691366
  43   3.70028037 -1.85027587
  44   3.67112178  1.89415966
  45   0.02378805 -0.27299500
  46   4.49973442  1.83030639
  47   3.51657950  1.55101962
  48   1.76995390  0.55991508
  49   3.13069656  1.88386644
  50   0.71509305  0.47535283
  51   0.83095573 -0.66629115
  52   1.91204478 -0.61300701
  53   0.39399106 -0.40605835
  54   2.55219844  1.13877110
  55   3.74197019 -1.84425404
  56   1.22441298  0.99518154
  57   1.23829405  0.70910732
  58   2.49773536 -1.31494268
  59   1.20743579 -0.95564814
  60   0.70314575  0.05765174
  61   2.84186590  0.70242910
  62   3.37314044  1.93126879
  63   2.67606665  1.03817707
  64  -0.45731133  0.26595370
  65   2.42386029  1.39875887
  66   3.48447125 -1.24210426
  67   3.00190494 -0.91485354
  68   2.25947467  1.31263394
  69  -0.65269512  0.77281928
  70   2.35291536 -1.03782104
  71   3.02439222 -1.82804482
  72   2.53261346 -1.43808362
  73   2.51687062 -1.13445834
  74   1.55503414 -0.08240574
  75   2.00706408 -1.21035863
  76   3.46362014  0.87742335
  77   2.85334522 -1.96846105
  78   0.47388675 -0.49804014
  79   2.46797386  0.05763083
  80   3.57229962 -1.99371778
  81   2.30504949  0.32641601
  82   0.80674585 -1.36837917
  83   1.23240656 -0.56388678
  84   2.46071835  0.58252751
  85   2.38276664  1.10329345
  86   1.72578145  0.25458737
  87   4.77191239 -1.06518641
  88   1.67802116 -1.64007793
  89   0.38115855 -1.65755174
  90   2.32768255 -0.77912652
  91   1.24353650  0.66970606
  92   2.81058307 -1.99904441
  93   1.56622386 -1.16572017
  94   4.69257480  1.73213651
  95   2.36328786  1.70257899
  96   1.73078868  0.93637720
  97   1.76252506 -0.66771207
  98   1.95288869  0.06025332
  99   2.33964920  0.97589859
  100  0.06257362  0.47663696