How does linear sequential unmasking differ from sequential unmasking?

Linear sequential unmasking is a specific approach that maintains restrictions on the number of changes that can be made during subsequent analyses, primarily based on the level of confidence in previous evaluations. This method integrates a structured process where analysts move through different phases of investigation, revealing information in a way that is designed to limit bias and prevent confirmation bias from influencing the decision-making process.

The principle behind restricting changes is to ensure that each step taken in the analysis builds on a firmly established foundation of understanding, which boosts the reliability of the outcomes. By tying modifications in analysis to confidence levels, linear sequential unmasking fosters a disciplined approach that enhances the integrity of the findings.

In contrast, other variations of unmasking may not impose such strict limitations, potentially allowing for an unrestricted number of changes, which can lead to less rigorous analysis and greater risk of bias. Therefore, the focus on confidence as a determinant for changes is what distinctly characterizes linear sequential unmasking.