# F4-conf-01 — Treatment effects and uncertainty extracted from two published tables

# Question

Extract, exactly as printed, specified point estimates, standard errors (SEs), 95% confidence-interval (CI) bounds and counts from (i) Armendariz (2026), arXiv:2609.27732v1 (staggered DiD of drug consumption room openings, Tables 6 and 7) and (ii) Li, Pearson-Merkowitz & Yokum (2026), arXiv:2606.14621v1 (RESEA RCT, Table 2). Each value gets a locator. I also derive a 95% CI from a printed SE and an SE from a printed CI, and I flag any requested quantity that the source does not print. Nothing is re-estimated.

# Data and exclusions

The only inputs were the two source extracts and data/README.md. Line counts are in n_input_rows: 134, 58 and 10 lines. The SHA-256 of each extract matches the README. No rows were excluded (out/exclusions.csv). All 25 requested items were assessed (n_analysed = 25). Six input issues are recorded in data_issues. The most relevant one: the same 5 km Callaway–Sant'Anna ATT of -0.431 has SE 0.210 in Table 6 but SE 0.218 in Appendix Table A19. Following the key definitions, I used Table 6. The other issues are:

• the number of control regions is 608 in some places and 640 in the A19 note;
• the abstract gives a 35% fall in fatal hospitalisations, while the body text gives about 30%;
• the RESEA text gives the weeks-on-UI CI as unsigned magnitudes, while the table gives signed values;
• the text has a "p ¡ 0.001" rendering defect;
• the extract editor re-set RESEA Table 2.

None of these issues changes any extracted value.

# Method

out/analysis.py parses the pipe-separated table lines, finds cells by row and column label, and prints each matched source line. It strips stars, $, thousands separators and parentheses, and keeps the sign. Values printed without decimals are stored as integers. JSON does not keep trailing zeros, so 0.210 is stored as 0.21 and -0.340 as -0.34. These are numerically identical, and the printed strings appear in the script's output. For the derived quantities:

• CI from SE: ATT ± 1.96 × SE (derivation_notes.dcr_att_5km_ci).
• SE from CI: (upper − lower) / (2 × 1.96) (derivation_notes.ri_wage_ate_se).

No randomness is involved (random_seed = null).

# Results

DCR study (log points)

• Observations at 5 km: dcr_obs_5km = 17250 region-years (Table 6).
• The HIV 5 km ATT has no star, so it is not marked significant at 10% (dcr_hiv_att_5km_significant_10pct = false).
• Its exact p-value is not reported in the extract, which prints only stars (dcr_hiv_att_5km_p_value = null).
• Derived 95% CI for the Table 6 5 km ATT: [dcr_att_5km_ci_low = -0.8426, dcr_att_5km_ci_high = -0.0194].

RESEA study, Table 2

• Wage ATE: ri_wage_ate = 1153 USD/yr, with printed 95% CI [ri_wage_ate_ci_low = 166, ri_wage_ate_ci_high = 2141].
• No SE is printed for the wage ATE (ri_wage_ate_se_reported = false). The SE derived from the CI is ri_wage_ate_se_derived = 503.83 USD/yr.
• Control-group mean wage: ri_control_mean_wage = 33043 USD/yr.
• Reemployment ATE: ri_reemployment_ate_pp = 1.47 pp.
• Weeks-on-UI ATE: ri_weeks_ui_ate = -1.99 weeks, with CI [ri_weeks_ui_ate_ci_low = -2.24, ri_weeks_ui_ate_ci_high = -1.75].

# Uncertainty

• DCR (Tables 6 and 7): uncertainty is printed as standard errors clustered at the MedStat region level, in parentheses. Significance stars mark p<0.01, p<0.05 and p<0.10. No CIs and no exact p-values are printed for the overall ATTs.
• RESEA (Table 2): uncertainty is printed as 95% confidence intervals with two-sided p-values. No standard errors are printed.
• What the derived quantities assume: both assume an approximately normal (Wald) estimator with critical value 1.96. The SE derivation also assumes the printed CI is symmetric. It is nearly so: 987 below and 988 above 1153. With N = 23,549, a t critical value would be practically identical.
• Check on the wage SE: the implied z = 1153/503.83 ≈ 2.29 gives p ≈ 0.022, matching the printed p (out/state/checks.md).
• Sensitivity of the DCR CI: the derived CI depends on using the Table 6 SE. With the A19 SE of 0.218 the interval would be wider. That alternative is not reported as a result.

# Limitations and open issues

• I could not produce an exact p-value for the HIV 5 km ATT (null). Computing one would need a distributional assumption, and the task asks for the printed value.
• The two DCR tables disagree on the 5 km ATT SE (0.210 vs 0.218). The extract does not explain why; I used Table 6 as instructed.
• The derived CI and SE are approximations under the conventions stated above, not values from the sources.
• The RESEA Table 2 layout was re-set by the extract editor. I relied on the editor saying the values are verbatim. As a cross-check, Table 3 repeats the wage ATE cell identically.
• I judged the task complete (feasibility = "complete"). The null p-value is the expected answer for a quantity the source does not report, not a failure.