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The data on forms is transferred to the CDMS tool through data entry. The most popular method being double data entry where two different data entry operators enter the data in the system independently and both the entries are compared by the system. In case the entry of a value conflicts, system alerts and a verification can be done manually.
Data type validation is customarily carried out on one or more simple data fields. The simplest kind of data type validation verifies that the individual characters provided through user input are consistent with the expected characters of one or more known primitive data types as defined in a programming language or data storage and retrieval ...
The data management plan describes the activities to be conducted in the course of processing data. Key topics to cover include the SOPs to be followed, the clinical data management system (CDMS) to be used, description of data sources, data handling processes, data transfer formats and process, and quality control procedure
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Data reconciliation is a technique that targets at correcting measurement errors that are due to measurement noise, i.e. random errors.From a statistical point of view the main assumption is that no systematic errors exist in the set of measurements, since they may bias the reconciliation results and reduce the robustness of the reconciliation.
A common data model (CDM) can refer to any standardised data model which allows for data and information exchange between different applications and data sources.Common data models aim to standardise logical infrastructure so that related applications can "operate on and share the same data", [1] and can be seen as a way to "organize data from many sources that are in different formats into a ...
A data clarification form (DCF) [1] or data query form is a questionnaire specifically used in clinical research. The DCF is the primary data clarification tool from the trial sponsor or contract research organization (CRO) towards the investigator to clarify discrepancies and ask the investigator for clarification.
A training data set is a data set of examples used during the learning process and is used to fit the parameters (e.g., weights) of, for example, a classifier. [9] [10]For classification tasks, a supervised learning algorithm looks at the training data set to determine, or learn, the optimal combinations of variables that will generate a good predictive model. [11]