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Tarefa paper_repro.thornton_2008.tab4_c1.design

paper_reproagentT3designépoca 1, tentativa 1Execução: 20261015T165744Z-suite-paper_repro-scripted-def9df

Veredito

passouPassou em todas as verificações obrigatórias.

Família do método (das chamadas de ferramentas): ols (regression)

Pergunta feita ao analista

Do small cash incentives raise the share of people in rural Malawi who return to learn their HIV test results? In the paper's main sample of respondents who were tested, estimate the effect of being offered any incentive on learning one's result, accounting for the fact that incentives were assigned to people within villages.

Resposta

Estimativa (infer.ols): coef.any = 0,4315.

Valores esperados e de onde vêm

thornton_2008.tab4_c1.software

Fonte
statsmodels 0.15.0: the reference specification of thornton_2008 tab4_c1 (infer.ols, figure 'coef.any') on an independent code path
Tipo
software
Localização
thornton_2008: Table 4 (Impact of monetary incentives and distance on learning HIV test results; dependent variable: attendance at HIV results centers), column (1) OLS, row 'Any incentive'
Valor
0,4314840.4314844809690622 (se 0,02290380.022903775310708543)
Conferido por
execução de software · sm.OLS(got, add_constant(['any', 'hiv2004', 'male', 'age', 'age2', 'rumphi', 'balaka']); 8 independent columns).fit(cov_type='cluster', groups=villnum) on thornton (the file pinned at sha256 1e05f2cda26106ca979ad70319cae69c237f9fd3369e429d86a4ec5062afb949, rows where MainSample == 1); n_obs = 2812. The tool infer.ols (magi_infer, numpy) does not call statsmodels. Written by scripts/paper_repro_reference.py.
Implementação
independente da ferramenta
Endereço
https://pypi.org/project/statsmodels/0.15.0/
  • #12 figura da resposta próxima: 0,4314840.4314844809690622 · relativa 0.000001 · absoluta 2.2903775310708542e-8
  • #13 figura da resposta próxima: 0,02290380.022903775310708543 · relativa 0.000001 · absoluta 2.2903775310708542e-8

thornton_2008.tab4_c1.paper

Fonte
Thornton, R. L. (2008). The Demand for, and Impact of, Learning HIV Status. American Economic Review 98(5): 1829-1863.
Tipo
paper
Localização
Table 4 (Impact of monetary incentives and distance on learning HIV test results; dependent variable: attendance at HIV results centers), column (1) OLS, row 'Any incentive'
Página
Table 4 (PMC3115776 author manuscript; AER page not read)
Trecho
Any incentive 0.431*** (0.023)
Valor como publicado
0.431
Erro-padrão como publicado
0.023
Valor
0,4310.431 (se 0,0230.023) share of respondents attending (probability)
Conferido por
fonte primária · Read on 2026-10-15 from the author manuscript in PubMed Central (PMC3115776, NIH public-access copy of the AER article), fetched as JATS XML through PMC's OAI-PMH service (sha256 b18201aa... of the record); the typeset AER PDF is behind the publisher's paywall and was not read. Table 4 column (1) OLS: Any incentive 0.431 (0.023); controls HIV, male, age (and age squared, per the notes), Rumphi and Balaka; sample size 2,812; the notes give robust standard errors clustered by village (119 villages) with district fixed effects. Data facts checked before any estimate: MainSample == 1 keeps 2,812 rows, all complete on these columns, in 119 villages.
sha256 da cópia lida
b18201aabb509714463119afab248ae22206f82d8d717c0efc20f24c33f5cc32 (identifica a cópia lida, não um arquivo canônico)
Endereço
https://pmc.ncbi.nlm.nih.gov/articles/PMC3115776/
Licença
Copyright American Economic Association (author manuscript in PMC); cited, not reproduced.
  • #14 figura da resposta próxima: 0,4310.431 · published_cell d=3 · absoluta 0.000500001
  • #15 figura da resposta próxima: 0,0230.023 · published_cell d=3 (the SE as printed) · absoluta 0.000500001

Verificações

Cada verificação, o que esperava, o que observou e a chamada que leu
#VerificaçãoObrigatóriaResultadoEsperadoObservadoTolerânciaFonteChamada
0resposta com lastro
every number backed
obrigatóriapassou—[]———
1figura da resposta escolhida
answer figure call_1b75cd1d:coef.any (infer.ols)
obrigatóriapassou—"call_1b75cd1d:coef.any"——call_1b75cd1d
2uma entre
tool_called(infer.ols): ok | tool_called(infer.ate): answer call is infer.ols | tool_called(infer.neyman): answer call is infer.ols
obrigatóriapassou[{"abs_tol":null,"bind":"answer_call","column":null,"failure_class":null,"field":"value","interval":false,"key":null,"kind":"tool_called","min_lre":null,"note":"","open_interval":false,"rel_tol":null,"required":true,"source_id":null,"table":null,"tool":"infer.ols","value":null,"weight":1,"where":null},{"abs_tol":null,"bind":"answer_call","column":null,"failure_class":null,"field":"value","interval":false,"key":null,"kind":"tool_called","min_lre":null,"note":"","open_interval":false,"rel_tol":null,"required":true,"source_id":null,"table":null,"tool":"infer.ate","value":null,"weight":1,"where":null},{"abs_tol":null,"bind":"answer_call","column":null,"failure_class":null,"field":"value","interval":false,"key":null,"kind":"tool_called","min_lre":null,"note":"","open_interval":false,"rel_tol":null,"required":true,"source_id":null,"table":null,"tool":"infer.neyman","value":null,"weight":1,"where":null}]"infer.ols"——call_1b75cd1d
3argumento igual
infer.ols.y = 'got'
obrigatóriapassou"got""got"——call_1b75cd1d
4argumento igual
infer.ols.x[0] = 'any'
obrigatóriapassou"any""any"——call_1b75cd1d
5argumento igual
not applicable: the answer call is infer.ols, not infer.ate
obrigatóriapassou"got"———call_1b75cd1d
6argumento igual
not applicable: the answer call is infer.ols, not infer.ate
obrigatóriapassou"any"———call_1b75cd1d
7argumento igual
not applicable: the answer call is infer.ols, not infer.neyman
obrigatóriapassou"got"———call_1b75cd1d
8argumento igual
not applicable: the answer call is infer.ols, not infer.neyman
obrigatóriapassou"any"———call_1b75cd1d
9argumento igual
infer.ols.y = 'got'
registradapassou"got""got"——call_1b75cd1d
10argumento igual
infer.ols.cluster = 'villnum'
registradapassou"villnum""villnum"——call_1b75cd1d
11diagnóstico
2812 vs 2812
registradapassou2.81228122.8122812default rel 1e-6 (abs floor 1e-6)—call_1b75cd1d
12figura da resposta próxima
0.431484481 vs 0.4314844809690622
registradapassou0,4314840.43148448096906220,4314840.43148448096904746relativa 0.000001 · absoluta 2.2903775310708542e-8thornton_2008.tab4_c1.softwarecall_1b75cd1d
13figura da resposta próxima
0.02290377531 vs 0.022903775310708543
registradapassou0,02290380.0229037753107085430,02290380.022903775310708474relativa 0.000001 · absoluta 2.2903775310708542e-8thornton_2008.tab4_c1.softwarecall_1b75cd1d
14figura da resposta próxima
0.431484481 vs 0.431
registradapassou0,4310.4310,4314840.43148448096904746published_cell d=3 · absoluta 0.000500001thornton_2008.tab4_c1.papercall_1b75cd1d
15figura da resposta próxima
0.02290377531 vs 0.023
registradapassou0,0230.0230,02290380.022903775310708474published_cell d=3 (the SE as printed) · absoluta 0.000500001thornton_2008.tab4_c1.papercall_1b75cd1d

Caminho de referência e caminho do agente

A chamada de referência ao lado da chamada que deu a resposta, argumento por argumento.

a tarefa T1 do mesmo alvo (paper_repro.thornton_2008.tab4_c1.tool)

Referência: infer.olsChamada do agente: infer.ols (call_1b75cd1d)igual
Argumentos da referência e do agente
ArgumentoReferênciaAgente
cluster"villnum""villnum"igual
controls["hiv2004","male","age","age2","rumphi","balaka"]["hiv2004","male","age","age2","rumphi","balaka"]igual
dataset"thornton""thornton"igual
fe[][]igual
intercept—truenão fixado pela referência
level—0,950.95não fixado pela referência
se—"HC1"não fixado pela referência
subset"MainSample == 1""MainSample == 1"igual
weights——não fixado pela referência
x["any"]["any"]igual
y"got""got"igual

Trajetória

Cada evento na ordem em que aconteceu: turnos do modelo, chamadas de ferramentas, guardas, transformações e pontuação.

  1. 0Início

    Do small cash incentives raise the share of people in rural Malawi who return to learn their HIV test results? In the paper's main sample of respondents who were tested, estimate the effect of being offered any incentive on learning one's result, accounting for the fact that incentives were assigned to people within villages.

    thornton (agent)

    Thornton's (2008) Malawi HIV-results experiment, as distributed with 'Causal Inference: The Mixtape' (thornton_hiv.dta): one row per respondent of the 2004 survey (4,820 rows, 133 columns; most are interactions not needed here). Columns used by the paper's main tables: villnum, village identifier (incentives were randomized to individuals within villages); site, district (1 Mchinji, 2 Balaka, 3 Rumphi); rumphi and balaka, 1 for respondents in those districts; got, 1 if the respondent went to the results centre and learned the HIV test result; any, 1 if the respondent was offered any nonzero monetary incentive; tinc, the value of the incentive offered; distvct, distance from home to the assigned results centre (km); under and over, 1 if that distance is under or over 1.5 km; simaverage, simulated average distance; hiv2004, 1 if HIV positive (0 negative; -1 or missing when not tested); test2004, 1 if tested in 2004; male, 1 for men; age, in years; age2, age squared; MainSample, 1 for the paper's main analysis sample (tested, with demographic data) and missing otherwise.

    file 1e05f2cda26106ca979ad70319cae69c237f9fd3369e429d86a4ec5062afb949 · frame —
  2. 1Turno do modelo
    call_132d9350referenceFim: tool_use0 ms0 de entrada · 0 de saída · 0 de raciocínio · 0 em cache
    Texto visível

    Table 4, column (1): OLS of attendance at the results centre on any incentive, HIV status, sex, age, age squared and district dummies, errors clustered by village, in the main sample (tested, with demographic data).

    Chamadas pedidas
    • infer.ols
      {
        "cluster": "villnum",
        "controls": [
          "hiv2004",
          "male",
          "age",
          "age2",
          "rumphi",
          "balaka"
        ],
        "dataset": "thornton",
        "fe": [],
        "subset": "MainSample == 1",
        "x": [
          "any"
        ],
        "y": "got"
      }
  3. 2Ferramenta
    infer.olsv0.1.0call_1b75cd1ddecidido pelo modeloreexecutável

    Motivo: Table 4, column (1): OLS of attendance at the results centre on any incentive, HIV status, sex, age, age squared and district dummies, errors clustered by village, in the main sample (tested, with demographic data).

    Argumentos
    {
      "cluster": "villnum",
      "controls": [
        "hiv2004",
        "male",
        "age",
        "age2",
        "rumphi",
        "balaka"
      ],
      "dataset": "thornton",
      "fe": [],
      "intercept": true,
      "level": 0.95,
      "se": "HC1",
      "subset": "MainSample == 1",
      "weights": null,
      "x": [
        "any"
      ],
      "y": "got"
    }
    Figuras call_1b75cd1d
    ChaveValorValor brutoErro-padrãoIC
    coef.any
    Coefficient on any in the regression of got
    0,431484 0.431484480969047460,02290380.0229037753107084740,386129 – 0,47684
    Diagnósticos
    • n_obs = 2.8122812
    • k = 88
    • r2 = 0,181360.1813597706906881
    • df_resid = 2.8042804
    • se_type = "cluster"
    • n_clusters = 119119
    Tabelas (1)
    {
      "coefficients": [
        {
          "ci_high": 0.46315992448391674,
          "ci_low": 0.2287466369483815,
          "coef": 0.3459532807161491,
          "p": 4.5941886333014205e-8,
          "se": 0.059187136420660445,
          "t": 5.845075495076448,
          "term": "Intercept"
        },
        {
          "ci_high": 0.47684019162042696,
          "ci_low": 0.38612877031766796,
          "coef": 0.43148448096904746,
          "p": 2.2667877103064597e-37,
          "se": 0.022903775310708474,
          "t": 18.839011259742424,
          "term": "any"
        },
        {
          "ci_high": 0.007346364068939702,
          "ci_low": -0.11645315494960973,
          "coef": -0.05455339544033501,
          "p": 0.08354447647717793,
          "se": 0.03125820681070506,
          "t": -1.745250320042415,
          "term": "hiv2004"
        },
        {
          "ci_high": 0.026959644688966417,
          "ci_low": -0.04646417870172913,
          "coef": -0.009752267006381356,
          "p": 0.5998437286886793,
          "se": 0.01853882046209857,
          "t": -0.5260457118250452,
          "term": "male"
        },
        {
          "ci_high": 0.010806472749021884,
          "ci_low": -0.001380706983903632,
          "coef": 0.004712882882559126,
          "p": 0.12830390998885716,
          "se": 0.003077147532971754,
          "t": 1.5315752111526681,
          "term": "age"
        },
        {
          "ci_high": 0.00004452430568361621,
          "ci_low": -0.00011913722431766311,
          "coef": -0.00003730645931702345,
          "p": 0.3684704324710839,
          "se": 0.00004132298729666214,
          "t": -0.9028016065052703,
          "term": "age2"
        },
        {
          "ci_high": -0.0792476627094785,
          "ci_low": -0.1949862230531265,
          "coef": -0.1371169428813025,
          "p": 0.000007340978823823163,
          "se": 0.029222891040900964,
          "t": -4.692107385589974,
          "term": "rumphi"
        },
        {
          "ci_high": -0.07180091213444206,
          "ci_low": -0.16396647992205243,
          "coef": -0.11788369602824725,
          "p": 0.0000015197747132819793,
          "se": 0.023270933534883274,
          "t": -5.065705501308697,
          "term": "balaka"
        }
      ]
    }
    Digests dos dados
    thornton dc13aacf7f58cce5e743c7dbaeafdfd387dc91212e8c2bbf48e7948d8ff682d7
    sha256 do resultado
    b9edb7ef8a6af8ff563d9d7944a6004ffd812d39aeafd09d05dba9a94a7b5763
  4. 3Turno do modelo
    call_283533edreferenceFim: tool_use0 ms0 de entrada · 0 de saída · 0 de raciocínio · 0 em cache
    Chamadas pedidas
    • submit_answer (meta-ferramenta)
      {
        "answer": "Estimativa (infer.ols): coef.any = 0,4315.",
        "caveats": [],
        "figure_refs": [
          "call_1b75cd1d:coef.any"
        ]
      }
  5. 4Guarda
    resposta aceita
    Números encontrados
    0,4315
    Sem lastro
    —
    Não citados
    —
    1 nova(s) tentativa(s) restante(s)
  6. 5Resposta

    Estimativa (infer.ols): coef.any = 0,4315.

    Figuras citadas: call_1b75cd1d:coef.any · Parada: answered
    Figura da resposta: call_1b75cd1d:coef.any = 0,4314840.43148448096904746 (se 0,02290380.022903775310708474)
  7. 6Pontuação
    #0resposta com lastropassouobrigatóriaevery number backed
  8. 7Pontuação
    #1figura da resposta escolhidapassouobrigatóriaanswer figure call_1b75cd1d:coef.any (infer.ols)
  9. 8Pontuação
    #2uma entrepassouobrigatóriatool_called(infer.ols): ok | tool_called(infer.ate): answer call is infer.ols | tool_called(infer.neyman): answer call is infer.ols
  10. 9Pontuação
    #3argumento igualpassouobrigatóriainfer.ols.y = 'got'
  11. 10Pontuação
    #4argumento igualpassouobrigatóriainfer.ols.x[0] = 'any'
  12. 11Pontuação
    #5argumento igualpassouobrigatórianot applicable: the answer call is infer.ols, not infer.ate
  13. 12Pontuação
    #6argumento igualpassouobrigatórianot applicable: the answer call is infer.ols, not infer.ate
  14. 13Pontuação
    #7argumento igualpassouobrigatórianot applicable: the answer call is infer.ols, not infer.neyman
  15. 14Pontuação
    #8argumento igualpassouobrigatórianot applicable: the answer call is infer.ols, not infer.neyman
  16. 15Pontuação
    #9argumento igualpassouregistradainfer.ols.y = 'got'
  17. 16Pontuação
    #10argumento igualpassouregistradainfer.ols.cluster = 'villnum'
  18. 17Pontuação
    #11diagnósticopassouregistrada2812 vs 2812
  19. 18Pontuação
    #12figura da resposta próximapassouregistrada0.431484481 vs 0.4314844809690622
  20. 19Pontuação
    #13figura da resposta próximapassouregistrada0.02290377531 vs 0.022903775310708543
  21. 20Pontuação
    #14figura da resposta próximapassouregistrada0.431484481 vs 0.431
  22. 21Pontuação
    #15figura da resposta próximapassouregistrada0.02290377531 vs 0.023

Épocas × verificações

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Época 1passoupassoupassoupassoupassoupassoupassoupassoupassoupassoupassoupassoupassoupassoupassoupassou

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