# Example 865 — The volunteers differed before they volunteered `the_volunteers_differed_before_they_volunteered.eml` - Employees who joined the wellness program are 20 points healthier than those who did not. The scores are real and the comparison is honest. What made someone a participant is computed below. ## EML ```eml # Self-authored for the EML case corpus (no external origin). Employees who # joined the wellness program are 20 points healthier than those who did not. The # scores are real and the comparison is honest. What made someone a participant is # computed below. # # The measurement is careful. It reads the real recorded health scores, not # self-reports; it covers every employee; the group comparison is the honest # difference of means; and the intent is exactly 'does the program improve # health'. # # Joining was voluntary, and the already health-conscious are the ones who joined, # so the participants were healthier before the program began - the after-gap # includes a gap that was there at the start. 500 => participants 500 => non_participants 75 => participant_before 80 => participant_after 62 => non_participant_before 60 => non_participant_after participant_after - non_participant_after => gap_after participant_before - non_participant_before => gap_before_the_program participant_after - participant_before => participant_change non_participant_after - non_participant_before => non_participant_change participant_change - non_participant_change => effect_by_change_from_baseline int(gap_before_the_program * 10000 / gap_after) => self_selection_share_per_myriad "participants : " + str(participants) ^0 "non-participants : " + str(non_participants) ^0 "" ^0 "participant health before / after : " + str(participant_before) + " / " + str(participant_after) ^0 "non-participant before / after : " + str(non_participant_before) + " / " + str(non_participant_after) ^0 "" ^0 "gap after the program : " + str(gap_after) ^0 "gap before the program : " + str(gap_before_the_program) ^0 "effect by change-from-baseline : " + str(effect_by_change_from_baseline) ^0 "pre-existing share of the gap : " + str(self_selection_share_per_myriad) + " per ten thousand" ^0 "" ^0 # ---- what the measurement verified ---- "the health comparison" ^0 " reads : real recorded health scores, not self-reports" ^0 " covers : every employee" ^0 " comparison : the honest difference of group means" ^0 " intent : does the program improve health" ^0 " employees omitted : 0" ^0 " verdict : PARTICIPANTS ARE 20 POINTS HEALTHIER" ^0 "" ^0 " reading real scores over every employee is the part done" ^0 " right here, and it is why the 20-point after-gap is a" ^0 " true difference between the two groups" ^0 "" ^0 # ---- what made someone a participant ---- "how the groups were formed" ^0 " the rule : each employee chose whether to join" ^0 " who chooses to join : the already health-conscious" ^0 " so at baseline the joiners were : 13 points healthier" ^0 " already, before any program" ^0 " what the after-gap contains : that pre-existing 13 plus" ^0 " whatever the program did" ^0 " what a cross-section cannot separate : the effect from" ^0 " who selected in" ^0 "" ^0 # ---- what the caller concluded ---- "the conclusion drawn" ^0 " program makes people : 20 points healthier" ^0 " gap that predated the program : " + str(gap_before_the_program) ^0 " effect once each group is measured against itself : " + str(effect_by_change_from_baseline) ^0 " are the scores wrong : no; they are exact" ^0 " is 20 the program's effect : no; " + str(self_selection_share_per_myriad) + " per ten" ^0 " thousand of it was there before the program" ^0 "" ^0 # ---- null control ---- # The same employees, compared as change-from-baseline (difference-in-differences), # or matched on their pre-program score, instead of a raw after-cross-section. 20 => nc_gap_by_raw_cross_section 7 => nc_effect_by_change_from_baseline 13 => nc_baseline_gap_the_matching_removes "null control - compare change-from-baseline, not the after-cross-section" ^0 " gap by raw after-cross-section : " + str(nc_gap_by_raw_cross_section) ^0 " effect by change-from-baseline : " + str(nc_effect_by_change_from_baseline) ^0 " baseline gap the matching removes : " + str(nc_baseline_gap_the_matching_removes) ^0 " no employee and no score changed; the 20 stopped being" ^0 " read as an effect and started being read against where" ^0 " each group began" ^0 "" ^0 # ---- the rule ---- "what a participant-vs-non-participant comparison guarantees" ^0 " the two groups differ by the measured amount now : exactly," ^0 " real scores, every employee, honest difference" ^0 " the program caused the difference : not addressed;" ^0 " joining was voluntary and the health-conscious joined," ^0 " so the groups differed by " + str(gap_before_the_program) + " at baseline - change-from-" ^0 " baseline leaves the program only " + str(effect_by_change_from_baseline) + " of the " + str(gap_after) ^0 "" ^0 "when the treated choose themselves, the groups differ before the treatment does" ^0 "anything, and a comparison taken only afterward measures who opted in as much as" ^0 "what they opted into; the baseline gap is charged to the program that did not" ^0 "open it" ^0 "" ^0 "It reads real scores over every employee with an honest group difference - the" ^0 "20-point gap is true. But joining was voluntary and the health-conscious joined," ^0 "so the groups differed by " + str(gap_before_the_program) + " at baseline; change-from-baseline leaves " + str(effect_by_change_from_baseline) + " for" ^0 "the program, " + str(self_selection_share_per_myriad) + " per ten thousand of the gap predating it." ^0 ``` ## Python (deterministic transpilation) ```python participants = 500 non_participants = 500 participant_before = 75 participant_after = 80 non_participant_before = 62 non_participant_after = 60 gap_after = participant_after - non_participant_after gap_before_the_program = participant_before - non_participant_before participant_change = participant_after - participant_before non_participant_change = non_participant_after - non_participant_before effect_by_change_from_baseline = participant_change - non_participant_change self_selection_share_per_myriad = int(gap_before_the_program * 10000 / gap_after) print("participants : " + str(participants)) print("non-participants : " + str(non_participants)) print("") print("participant health before / after : " + str(participant_before) + " / " + str(participant_after)) print("non-participant before / after : " + str(non_participant_before) + " / " + str(non_participant_after)) print("") print("gap after the program : " + str(gap_after)) print("gap before the program : " + str(gap_before_the_program)) print("effect by change-from-baseline : " + str(effect_by_change_from_baseline)) print("pre-existing share of the gap : " + str(self_selection_share_per_myriad) + " per ten thousand") print("") print("the health comparison") print(" reads : real recorded health scores, not self-reports") print(" covers : every employee") print(" comparison : the honest difference of group means") print(" intent : does the program improve health") print(" employees omitted : 0") print(" verdict : PARTICIPANTS ARE 20 POINTS HEALTHIER") print("") print(" reading real scores over every employee is the part done") print(" right here, and it is why the 20-point after-gap is a") print(" true difference between the two groups") print("") print("how the groups were formed") print(" the rule : each employee chose whether to join") print(" who chooses to join : the already health-conscious") print(" so at baseline the joiners were : 13 points healthier") print(" already, before any program") print(" what the after-gap contains : that pre-existing 13 plus") print(" whatever the program did") print(" what a cross-section cannot separate : the effect from") print(" who selected in") print("") print("the conclusion drawn") print(" program makes people : 20 points healthier") print(" gap that predated the program : " + str(gap_before_the_program)) print(" effect once each group is measured against itself : " + str(effect_by_change_from_baseline)) print(" are the scores wrong : no; they are exact") print(" is 20 the program's effect : no; " + str(self_selection_share_per_myriad) + " per ten") print(" thousand of it was there before the program") print("") nc_gap_by_raw_cross_section = 20 nc_effect_by_change_from_baseline = 7 nc_baseline_gap_the_matching_removes = 13 print("null control - compare change-from-baseline, not the after-cross-section") print(" gap by raw after-cross-section : " + str(nc_gap_by_raw_cross_section)) print(" effect by change-from-baseline : " + str(nc_effect_by_change_from_baseline)) print(" baseline gap the matching removes : " + str(nc_baseline_gap_the_matching_removes)) print(" no employee and no score changed; the 20 stopped being") print(" read as an effect and started being read against where") print(" each group began") print("") print("what a participant-vs-non-participant comparison guarantees") print(" the two groups differ by the measured amount now : exactly,") print(" real scores, every employee, honest difference") print(" the program caused the difference : not addressed;") print(" joining was voluntary and the health-conscious joined,") print(" so the groups differed by " + str(gap_before_the_program) + " at baseline - change-from-") print(" baseline leaves the program only " + str(effect_by_change_from_baseline) + " of the " + str(gap_after)) print("") print("when the treated choose themselves, the groups differ before the treatment does") print("anything, and a comparison taken only afterward measures who opted in as much as") print("what they opted into; the baseline gap is charged to the program that did not") print("open it") print("") print("It reads real scores over every employee with an honest group difference - the") print("20-point gap is true. But joining was voluntary and the health-conscious joined,") print("so the groups differed by " + str(gap_before_the_program) + " at baseline; change-from-baseline leaves " + str(effect_by_change_from_baseline) + " for") print("the program, " + str(self_selection_share_per_myriad) + " per ten thousand of the gap predating it.") ``` ## stdout (executed) ```text participants : 500 non-participants : 500 participant health before / after : 75 / 80 non-participant before / after : 62 / 60 gap after the program : 20 gap before the program : 13 effect by change-from-baseline : 7 pre-existing share of the gap : 6500 per ten thousand the health comparison reads : real recorded health scores, not self-reports covers : every employee comparison : the honest difference of group means intent : does the program improve health employees omitted : 0 verdict : PARTICIPANTS ARE 20 POINTS HEALTHIER reading real scores over every employee is the part done right here, and it is why the 20-point after-gap is a true difference between the two groups how the groups were formed the rule : each employee chose whether to join who chooses to join : the already health-conscious so at baseline the joiners were : 13 points healthier already, before any program what the after-gap contains : that pre-existing 13 plus whatever the program did what a cross-section cannot separate : the effect from who selected in the conclusion drawn program makes people : 20 points healthier gap that predated the program : 13 effect once each group is measured against itself : 7 are the scores wrong : no; they are exact is 20 the program's effect : no; 6500 per ten thousand of it was there before the program null control - compare change-from-baseline, not the after-cross-section gap by raw after-cross-section : 20 effect by change-from-baseline : 7 baseline gap the matching removes : 13 no employee and no score changed; the 20 stopped being read as an effect and started being read against where each group began what a participant-vs-non-participant comparison guarantees the two groups differ by the measured amount now : exactly, real scores, every employee, honest difference the program caused the difference : not addressed; joining was voluntary and the health-conscious joined, so the groups differed by 13 at baseline - change-from- baseline leaves the program only 7 of the 20 when the treated choose themselves, the groups differ before the treatment does anything, and a comparison taken only afterward measures who opted in as much as what they opted into; the baseline gap is charged to the program that did not open it It reads real scores over every employee with an honest group difference - the 20-point gap is true. But joining was voluntary and the health-conscious joined, so the groups differed by 13 at baseline; change-from-baseline leaves 7 for the program, 6500 per ten thousand of the gap predating it. ``` ## Round-trip `ok: true` — round-trip fixpoint reached (python1 == python2) ## Trace event types eml:run:start · eml:assign · eml:output · eml:run:done