What type of data structure has one or more records per subject, per analysis parameter, and per analysis timepoint?

The correct answer is a basic data structure. In clinical trials, a basic data structure is designed to maintain detailed records for each individual subject across various parameters and time points. This means that for each subject's participation in the trial, there can be multiple entries or records that correspond to different analysis parameters (such as vital signs or lab results) and time points (such as visits or assessments throughout the study duration).

This type of data structure is essential for capturing the complexity and variability inherent in clinical trial data, allowing researchers to perform detailed analyses that take into account the longitudinal aspect of data collection for each subject. By organizing data in this manner, it simplifies the process of summarizing and analyzing the data for each subject over time.

Derived data structures, on the other hand, typically contain calculated or processed information derived from the basic structured data, which focuses on summary or aggregated results rather than maintaining raw or detailed records. Aggregated data structures, in contrast, consolidate data into summary statistics making it less suitable for representing multiple records per subject or time point. Hierarchical data structures may also organize data but are generally used for representing relationships that involve multiple levels or nesting rather than focusing directly on the subject-analysis-parameter-timepoint trio.