The Seven Steps of Data Evaluation

Validation and review processes, different as they may be in the level of diligence, follow the same basic steps of consecutive examination of a data package to establish the following facts  

Each data package representing a group of samples analyzed with one method is evaluated separately. The end product of data evaluation is an assessment of several 

PARCC parameters (typically, accuracy, precision, and representativeness) for the samples in the reviewed data package. A checklist prompts a structured approach to data evaluation and allows documenting deficiencies. Appendices 23, 24, and 25 contain examples of such checklists for organic, trace element, and inorganic analyses. 

In the course of data evaluation, the chemist will make decisions on data quality by relying not only on acceptance criteria but also using the knowledge of physical and chemical properties of the target analytes and their fate in the sampled matrix. The chemist s professional expertise and judgment play a major role in data evaluation. 

This chapter describes the process of data evaluation that is equivalent to data validation Level 3. It may be scaled up to validation Level 4 by including a thorough examination of raw data and the recalculation of results or scaled down to cursory data review. 

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D1 Data review, verification, and validation D2 Validation and verification methods 4.3.5 Data reduction, verification, and reporting 4.3.6 Internal data review 5.1 Data evaluation 5.2 The seven steps of data evaluation... 

Figure 5.2 The seven steps of data evaluation process.

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