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Diagrams that represent study schemas generally conceive of time as moving from left to right, using horizontal lines to represent periods of time and slanting lines to represent branches into separate treatmentsarms, convergence into a common follow-up, or crossover to a different treatment.

In this type of document, diagrams are drawn using "blocks" corresponding to trial elements rather than horizontal lines. Trial elements are are the various treatment and non-treatment time periods of the trial and we want to emphasize the separate trial elements might otherwise be "hidden" in a single horizontal line. See Section 7.2.2, Trial the Section on Trial Elements (TE), for more information about defining trial elements. In general, the elements of a trial will be fairly clear. However, in the process of working out a trial design, alternative definitions of trial elements may be considered, in which case diagrams for each alternative may be constructed.

In the study schema diagrams in this example, the only slanting lines used are those that represent branches (i.e., decision points where subjects are divided into separate treatment groups). One advantage of this style of diagram, which does not show convergence of separate paths into a single block, is that the number of arms in the trial can be determined by counting the number of parallel paths at the right end of the diagram.

As illustrated in the study schema diagram for Example Trial 1, this simple parallel trial has 3 arms, corresponding to the 3 possible left-to-right "paths" through the trial. Each path corresponds to 1 of the 3 treatment elements at elements at the right end of the diagram. Randomization is represented by the 3 red arrows leading from the Run-in block.

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Trial Design Matrix

For Example Trial 1, the conversion of the trial design matrix into the TA dataset is straightforward. For each cell of the matrix, there is a record in the TA dataset. ARM, EPOCH, and ELEMENT can be populated directly from the matrix. TAETORD acts as a sequence number for the elements within an arm, so it can be populated by counting across the cells in the matrix. The randomization information, which is not represented in the trial design matrix, is held in TABRANCH in the TA dataset. TABRANCH is populated only if there is a branch at the end of an element for the arm. When TABRANCH is populated, it describes how the decision at the branch point would result in a subject being in this arm.