Row 50517
Content Data
This page contains data entry 50517 from the Axioma AXP content repository. The structured data below represents the complete record for this entry.
Check out dagitty.net. This will allow you to draw out your theoretical causal model and then do the do-calculus to tell you what measured (and unmeasured) variables you need to adjust for to estimate the causal effect.
Then build your model with those covariates, recognizing any coeffients on the adjustment set are NOT causal effects for those specific variables. The coefficient on your exposure will be what you're looking for, but you should consider simulating out counterfactuals for your usual data with the full model.
| Field | Value |
|---|---|
| text | Check out dagitty.net. This will allow you to draw out your theoretical causal model and then do the do-calculus to tell you what measured (and unmeasured) variables you need to adjust for to estimate the causal effect. Then build your model with those covariates, recognizing any coeffients on the adjustment set are NOT causal effects for those specific variables. The coefficient on your exposure will be what you're looking for, but you should consider simulating out counterfactuals for your us… |
| label | r/datascience |
| dataType | comment |
| communityName | r/datascience |
| datetime | 2024-05-22 |
| username_encoded | Z0FBQUFBQm5Lak1TWk9NdlU5UFZTYlFhREdNcU9KSGhDMmNLSnd3YkZlellnZU5yVmIwMjhwOVl3V1lIUUVSNHZyR054cjNjN3kwcEF1UTNXN2ZCWHZPcW1RVlZzY1lDc1VXSnNGa2gxMkMxVzVVdWp5bnpQSGs9 |
| url_encoded | Z0FBQUFBQm5Lak9pUjhiS3VkN3RhVWF4ejBtdVhNWFRKcDN6ZGowWi1OQzAxYWlUanVKNmlWUlBMMzg5Wld3Z01yV3pOLTRrZ0I5a3JmQkV2QmRpVzZZd1hVbWVsT0dHUEpuNHBaYnlZMkJEMlZqT0NVMkg5SDU3SmNfdlR0Tnk4blNuWDQ3bGxBcnVkV1A0RXVqV2Y2cmFjczdxUFhLUmtKa0RmYjNLRHJOWHZMOTI1Zjg4NlpEYU1qaGd1ZzA2a05Kc3dFOHNYQ1JMTDRhRmtCb1BBWjRadkpkdHVNcU9HZz09 |
Raw Record
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"text": "Check out dagitty.net. This will allow you to draw out your theoretical causal model and then do the do-calculus to tell you what measured (and unmeasured) variables you need to adjust for to estimate the causal effect.\n\nThen build your model with those covariates, recognizing any coeffients on the adjustment set are NOT causal effects for those specific variables. The coefficient on your exposure will be what you're looking for, but you should consider simulating out counterfactuals for your usual data with the full model.",
"label": "r/datascience",
"dataType": "comment",
"communityName": "r/datascience",
"datetime": "2024-05-22",
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}
Entry Information
- Entry ID: 50517
- Repository: Axioma AXP
- Dataset: arrmlet/reddit_dataset_36
- Total Entries: 100,000