Tarefa causcibench_real.q049

Veredito

Pergunta feita ao analista

What is the effect of Medicaid eligibility expansions on drug overdose mortality per 100,000 among adults aged 25–64 for the years 1999 and 2008?

Como o agente resolveu e como foi validado

Resumo passo a passo do que o agente executou, por que o caminho está correto e como cada verificação conferiu o resultado.

1. 1Preparação da base de dados
   venkatramani_early_medicaid— This dataset links state-year mortality from drug overdoses to population denominators and state socioeconomic and policy measures to study patterns in overdose deaths before and after early coverage changes. The unit of observation is the state-year, with deaths aggregated at the state level and mortality rates constructed per 100,000 population. Crude and age-adjusted overdose rates are provided alongside population counts to support rate construction and standardization. Geographic identifiers use state FIPS codes, and monetary and policy variables capture contemporaneous state conditions. Variables include: year: Calendar year of observation for the state-year record deaths_drugod: Count of deaths attributed to drug overdose in the state-year crude_drugod: Crude drug overdose mortality rate per 100,000 population in the state-year ageadjust_drugod: Age-adjusted drug overdose mortality rate per 100,000 population in the state-year statefips: Two-digit FIPS code identifying the state pop: State population count used as the denominator for rate calculations in the corresponding year unemp_rate: State unemployment rate (percent) in the corresponding year welf_fs_4p_benefit: Benefit level for a four-person household under state welfare/food assistance programs in the corresponding year ssi_total: Aggregate Supplemental Security Income (SSI) disbursements or caseload-related total at the state-year level pov_rate: State poverty rate (percent) in the corresponding year state_min_wage: State minimum wage level in dollars in the corresponding year expansion: Indicator equal to 1 in state-years after implementation of an early eligibility expansion for low-income adults, and 0 otherwise exp_st: Indicator equal to 1 for states that undertook an early eligibility expansion neighbor_st: Indicator equal to 1 for states that share a land border with an early expansion state
2. 2Chamada que gerou a resposta finalinfer.ols(Regressão linear por mínimos quadrados ordinários (MQO))citada na respostacoincide com a referência

   Ver chamada call_f78e3277 nos detalhes

   causcibench_metadata_rule/1: did

   Por que este é o caminho de referência: causcibench_metadata_rule/1: did
   Argumentos principais

   controls:

   ["unemp_rate","pov_rate"]

   dataset:

   "venkatramani_early_medicaid"

   fe:

   ["statefips","year"]

   intercept:

   true

   level:

   0,950.95

   se:

   "HC1"

   x:

   ["expansion"]

   y:

   "ageadjust_drugod"

   Resultado calculado

   • coef.expansion = -3,35169 -3.351685773549289
     Coefficient on expansion in the regression of ageadjust_drugod
   Diagnósticos: n_obs = 1.7131713 (observations used) · k = 8787 (parameters estimated, fixed-effect dummies included) · r2 = 0,9119240.9119237637324413 · df_resid = 1.6261626 · se_type = "HC1" (heteroskedasticity-robust standard errors (HC1)) · fixed_effects = "statefips (51 levels), year (34 levels)" (absorbed as dummies; their coefficients are not tabulated)
3. 3Conferência de lastro e resposta final

   Todos os 1 números escritos na resposta foram conferidos contra as ferramentas e o enunciado (nenhum número sem lastro).

   Números encontrados: -3,352
   Figuras citadas: call_f78e3277:coef.expansion
   • ✓
     #0resposta com lastro

     every number in the answer was stated by a tool call
   • ✗
     #1figura da resposta próxima

     CauSciBench effect accuracy: |answer figure − gold| ≤ 5% of |gold|

Valores esperados e de onde vêm

Verificações

Caminho de referência e caminho do agente

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

Trajetória

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

1. 0Início

   What is the effect of Medicaid eligibility expansions on drug overdose mortality per 100,000 among adults aged 25–64 for the years 1999 and 2008?

   venkatramani_early_medicaid (agent)

   This dataset links state-year mortality from drug overdoses to population denominators and state socioeconomic and policy measures to study patterns in overdose deaths before and after early coverage changes. The unit of observation is the state-year, with deaths aggregated at the state level and mortality rates constructed per 100,000 population. Crude and age-adjusted overdose rates are provided alongside population counts to support rate construction and standardization. Geographic identifiers use state FIPS codes, and monetary and policy variables capture contemporaneous state conditions. Variables include: year: Calendar year of observation for the state-year record deaths_drugod: Count of deaths attributed to drug overdose in the state-year crude_drugod: Crude drug overdose mortality rate per 100,000 population in the state-year ageadjust_drugod: Age-adjusted drug overdose mortality rate per 100,000 population in the state-year statefips: Two-digit FIPS code identifying the state pop: State population count used as the denominator for rate calculations in the corresponding year unemp_rate: State unemployment rate (percent) in the corresponding year welf_fs_4p_benefit: Benefit level for a four-person household under state welfare/food assistance programs in the corresponding year ssi_total: Aggregate Supplemental Security Income (SSI) disbursements or caseload-related total at the state-year level pov_rate: State poverty rate (percent) in the corresponding year state_min_wage: State minimum wage level in dollars in the corresponding year expansion: Indicator equal to 1 in state-years after implementation of an early eligibility expansion for low-income adults, and 0 otherwise exp_st: Indicator equal to 1 for states that undertook an early eligibility expansion neighbor_st: Indicator equal to 1 for states that share a land border with an early expansion state

   file dee9b05cee4a75414abe6d4bad0127a61bc4480035d05324d4d3fb3cdcbb1039 · frame —
2. 1Turno do modelo
   call_7c0b99d5referenceFim: tool_use0 ms0 de entrada · 0 de saída · 0 de raciocínio · 0 em cache

   Texto visível

   causcibench_metadata_rule/1: did

   Chamadas pedidas

   • infer.ols

     {
       "controls": [
         "unemp_rate",
         "pov_rate"
       ],
       "dataset": "venkatramani_early_medicaid",
       "fe": [
         "statefips",
         "year"
       ],
       "x": [
         "expansion"
       ],
       "y": "ageadjust_drugod"
     }

   Mensagens (formato neutro)Instruções do sistemaFerramentas oferecidas
3. 2Ferramenta
   infer.ols— Regressão linear por mínimos quadrados ordinários (MQO)v0.1.0call_f78e3277decidido pelo modeloreexecutável

   Motivo: causcibench_metadata_rule/1: did

   Argumentos

   {
     "cluster": null,
     "controls": [
       "unemp_rate",
       "pov_rate"
     ],
     "dataset": "venkatramani_early_medicaid",
     "fe": [
       "statefips",
       "year"
     ],
     "intercept": true,
     "level": 0.95,
     "se": "HC1",
     "subset": null,
     "weights": null,
     "x": [
       "expansion"
     ],
     "y": "ageadjust_drugod"
   }

   Figuras call_f78e3277

   Chave	Valor	Valor bruto	Erro-padrão	IC
   coef.expansion Coefficient on expansion in the regression of ageadjust_drugod	-3,35169	-3.351685773549289	1,150581.1505838418721415	-5,60847 – -1,0949

   Diagnósticos

   • n_obs = 1.7131713 (observations used)
   • k = 8787 (parameters estimated, fixed-effect dummies included)
   • r2 = 0,9119240.9119237637324413
   • df_resid = 1.6261626
   • se_type = "HC1" (heteroskedasticity-robust standard errors (HC1))
   • n_clusters = — (errors not clustered)
   • fixed_effects = "statefips (51 levels), year (34 levels)" (absorbed as dummies; their coefficients are not tabulated)

   Derivação matemática e pressupostos

   coef.expansion

   1. Coeficiente de expansion na regressão por mínimos quadrados ordinários de ageadjust_drugod, efeitos fixos de statefips, year.→ -3,35169 (-3.351685773549289)
   2. Erro-padrão robusto à heterocedasticidade (HC1): a raiz da variância estimada do coeficiente.ep = √V_jj→ 1,15058 (1.1505838418721415)
   3. Intervalo de 95% de confiança: a estimativa mais ou menos o valor crítico da distribuição t de Student com 1626 graus de liberdade vezes o erro-padrão.IC = β ± c · ep

   Pressupostos do estimador

   • the conditional mean of the outcome is linear in the regressors
   • errors are independent across observations; their variance may differ

   Tabelas (1)

   {
     "coefficients": [
       {
         "ci_high": 5.0543823817376365,
         "ci_low": -0.9574008288747962,
         "coef": 2.04849077643142,
         "p": 0.18150934987669956,
         "se": 1.5325047433447525,
         "t": 1.336694574896067,
         "term": "Intercept"
       },
       {
         "ci_high": -1.0949029958750973,
         "ci_low": -5.60846855122348,
         "coef": -3.351685773549289,
         "p": 0.003628264636810602,
         "se": 1.1505838418721415,
         "t": -2.913030455995005,
         "term": "expansion"
       },
       {
         "ci_high": -0.38135460379004876,
         "ci_low": -0.9704730413723013,
         "coef": -0.675913822581175,
         "p": 0.00000725075505790007,
         "se": 0.15017620701839626,
         "t": -4.500804994351582,
         "term": "unemp_rate"
       },
       {
         "ci_high": 0.34141572975482026,
         "ci_low": 0.0785141917415105,
         "coef": 0.20996496074816537,
         "p": 0.0017613854675344078,
         "se": 0.06701802775036925,
         "t": 3.1329623952863717,
         "term": "pov_rate"
       }
     ]
   }

   • 430 rows were dropped because one of 'ageadjust_drugod', 'expansion', 'unemp_rate', 'pov_rate', 'statefips', 'year' was missing

   Hashes SHA-256 e metadados de reprodução

   Digests dos dados

   venkatramani_early_medicaid 2a158981689789ad028fb63897c1a54a8034e1b67e32461a3fc7a79270bdaeeb

   sha256 do resultado

   4c75b202f6bead23d4ff45e90abdab9235078a09826c02412c5c152cec04fb4a

   Resultado mostrado ao modelo
4. 3Turno do modelo
   call_d2daace4referenceFim: 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.expansion = -3,352.",
       "caveats": [],
       "figure_refs": [
         "call_f78e3277:coef.expansion"
       ]
     }

   Mensagens (formato neutro)Instruções do sistemaFerramentas oferecidas
5. 4Guarda
   resposta aceita

   Números encontrados

   -3,352

   Sem lastro

   —

   Não citados

   —

   1 nova(s) tentativa(s) restante(s)
6. 5Resposta

   Estimativa (infer.ols): coef.expansion = -3,352.

   Figuras citadas: call_f78e3277:coef.expansion · Parada: answered

   Figura da resposta: call_f78e3277:coef.expansion = -3,35169-3.351685773549289 (se 1,150581.1505838418721415)
7. 6Pontuação
   #0resposta com lastropassouobrigatóriaevery number backed
8. 7Pontuação
   #1figura da resposta próximafalhouobrigatória-3.351685774 vs -3.727

Épocas × verificações

Tentativas

Cada tentativa é seu próprio arquivo e é publicada; só a última de cada época é pontuada.

• época 1, tentativa 1falhoupontuada(exibindo)

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