Continuous Variable Adjustment for Confounder-Aware Correlation Analysis
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Solution Overview
Problem
Current methods struggle to identify correlations between continuous variables and dependent variables when confounders are present, leading to difficulties in analyzing the relationship between these variables.
Innovation Solution
A method and apparatus that determine confounders from analysis data, classify data into subgroups based on confounder combinations, and generate new continuous variables by setting a representative value to '0', allowing for the transformation of continuous variables into relative values, enabling the analysis of correlations between the new continuous variables and dependent variables.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If confounders are adjusted using conventional methods, then the confounding effect is reduced, but the correlation between continuous variable and dependent variable remains undetected
Solution Approach 1:
The patent transforms the continuous variable into a new continuous variable by applying parameter changes based on confounder values. Specifically, it calculates a transformed value using the formula: new_continuous_variable = original_continuous_variable - (confounder_effect_coefficient × confounder_value). This parameter transformation adjusts the continuous variable to account for confounder influences while preserving the underlying correlation structure, thereby resolving the contradiction between reliable confounder adjustment and accurate correlation detection.
2Object-affected harmful factors
If the continuous variable is adjusted to account for confounders, then the confounding influence is minimized, but the ability to identify existing correlations is lost
Solution Approach 1:
The patent introduces a new continuous variable as an intermediary that mediates between the original continuous variable and the dependent variable. This new variable serves as a transformed representation that has had confounder effects partially removed while maintaining the essential correlation information. By using this intermediary variable for analysis, the method minimizes confounder influence without losing the underlying correlation signal.
3Ease of operation
If conventional confounder adjustment methods are used, then the analysis is simple, but the correlation analysis accuracy deteriorates when confounders are present
Solution Approach 1:
The patent applies parameter changes to the continuous variable by transforming it using confounder-related parameters. The transformation formula new_continuous_variable = original_continuous_variable - (confounder_effect_coefficient × confounder_value) modifies the parameter representation of the continuous variable while maintaining computational simplicity. This approach preserves ease of operation through straightforward calculation while significantly improving correlation analysis accuracy in the presence of confounders.
Data Source
AI summary
Provided are a method for adjusting a continuous variable, a method and an apparatus for analyzing a correlation using the same. A method for adjusting a continuous variable according to an exemplary embodiment of the present disclosure is a method for adjusting a continuous variable by an apparatus including: determining at least one confounder from analysis data; classifying the analysis data into a plurality of subgroups having the same combination of confounders; and generating a new continuous variable for each subgroup based on a representative value of a continuous variable distribution.