{
  "context": "This criteria evaluates how well the engineer uses the spreg package to perform spatial diagnostic testing on regression models. The focus is on proper usage of OLS regression with spatial diagnostics enabled, and correct interpretation of Lagrange Multiplier tests for spatial error and spatial lag dependence.",
  "type": "weighted_checklist",
  "checklist": [
    {
      "name": "OLS Model Setup",
      "description": "Uses spreg.OLS class to create the initial regression model with dependent variable y, independent variables X, and spatial weights matrix w as parameters",
      "max_score": 20
    },
    {
      "name": "Spatial Diagnostics Enabled",
      "description": "Sets spat_diag=True parameter when creating the OLS model to enable spatial diagnostic tests, which is required to generate LM test statistics",
      "max_score": 15
    },
    {
      "name": "LM Error Extraction",
      "description": "Accesses the LM test for spatial error autocorrelation from the model's diagnostic attributes (e.g., model.lm_error), extracting both test statistic and p-value",
      "max_score": 25
    },
    {
      "name": "LM Lag Extraction",
      "description": "Accesses the LM test for spatial lag dependence from the model's diagnostic attributes (e.g., model.lm_lag), extracting both test statistic and p-value",
      "max_score": 25
    },
    {
      "name": "Test Interpretation",
      "description": "Correctly interprets p-values from LM tests by comparing against significance threshold (0.05) to determine whether spatial error or spatial lag models are needed, providing appropriate recommendations based on test results",
      "max_score": 15
    }
  ]
}