| CPC G06F 16/211 (2019.01) | 12 Claims |

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1. A processor-implemented method of joining two or more research studies to extract analytical insights for enabling cross-study analysis, the method comprising:
identifying, using an identification module, at least one matched variable in a statistically representative sample in each of the two or more research studies;
establishing, using a segment establishing module, for each combination of matched variables, a schema of segments, from the two or more research studies; and
creating a joint study, using a joint study creation module, by combining responses from each of the two or more research studies within each segment of the statistically representative schema of segments,
wherein a step of creating the joint study, in turn, comprises:
determining a combination of matched variable segments associated with the highest number of variables, that have statistically representative samples based on a predetermined confidence level;
receiving a user-selected variable to import and determine one or more variables that are related with each other and establish terms of relationship between the one or more variables; and
changing outliers and unexpected values to be within a predetermined range and delete erroneous data, for combining responses from each of the two or more research studies within each segment of the statistically representative schema of segments.
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