Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: Most probability-based methods used to link records from two distinct data sets corresponding to the same target population do not lead to perfect linkage, i.e. there are linkage errors in the merged data. Further, the linkage is often incomplete, in the sense that many records in the two data sets remain unmatched at the completion of the linkage process.  introduces methods that correct for the biases due to linkage errors and incomplete linkage when carrying out regression analysis using linked data. In particular, it focuses on the case where one of the linked data sets is a sample from the target population and the other is a register, i.e. it covers the entire target population.
['Gunky Kim', 'Ray Chambers']
I am writing a research paper on a idea Regression analysis under incomplete linkage
[{"from": "human", "value": "I am writing a research paper on a idea Regression analysis under incomplete linkage"}, {"from": "gpt", "value": "Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: Most probability-based methods used to link records from two distinct data sets corresponding to the same target population do not lead to perfect linkage, i.e. there are linkage errors in the merged data. Further, the linkage is often incomplete, in the sense that many records in the two data sets remain unmatched at the completion of the linkage process.  introduces methods that correct for the biases due to linkage errors and incomplete linkage when carrying out regression analysis using linked data. In particular, it focuses on the case where one of the linked data sets is a sample from the target population and the other is a register, i.e. it covers the entire target population."}]