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While traditional methods such as randomization, matching, and stratification remain effective for controlling confounding, newer techniques like latent variable modeling with negative controls and machine learning methods such as LASSO, Ridge regression, and random forests offer enhanced flexibility and adaptability

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It assists researchers to determine the effectiveness of the process and outcome measures defined

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