Answer to Question #269741 in Management for tiiso

Question

Validity and reliability are key concepts to quality of monitoring and evaluation data, and these are applied depending on the type of data at hand. Explain data processes for each type that you deploy to ensure sound conclusions in M&E.                                                                            

Answer 1

Validity refers to the extent to which a measure represents what we intend to measure. Though simple in principle, validity can be difficult to assess in practice, particularly when measuring social phenomena. Reliability refers to the stability of a measurement process. Two methods are commonly used to estimate reliability test/retest and internal consistency measurement. Validity is an indication of how well an instrument measures what it is truly supposed to measure. Validity is a data quality dimension that refers to information that doesn't conform to a specific format or follow business rules. To meet this data quality dimension, you must check if all of your information follows a specific format or business rules.

Reliability. In the realm of data quality characteristics, reliability means that a piece of information doesn't contradict another piece of information in a different source or system. Reliability is a vital data quality characteristic. Monitoring efforts strive to generate high-quality information. Quality assurance (QA) and quality control (QC) are processes that ensure data integrity and minimize errors. QA and QC occur throughout the monitoring process. Reliability can be estimated by comparing different versions of the same measurement. Validity is harder to assess, but it can be estimated by comparing the results to other relevant data or theories. Methods of estimating reliability and validity are usually split up into different types.