What are the most effective strategies for managing quality control on quantitative methods in program evaluation? Why are they the most effective?

Managing quality control when using quantitative methods, in evaluations, is important. The evaluation using the quantitative method must show validity, reliability, and transparency.

Evaluators must use methods that have been used previously and that have been proven to return valid and reliable data. The evaluation must also be transparent, evaluators must document everything that is done, as well as all results and how they were analyzed (Bryman, Becker, &Sempik, 2008). This information must be available so that others can tell where the data come from and how conclusions were drawn for the data.

The evaluator must also understand the theoretical process(s) involved in the data collection and analyzation that lead to the assumptions made by the statistical processes involved in quantitative analysis. If the theoretical processes are not understood then there is a higher likeliness that the conclusions that are drawn will be faulty.

The evaluator must be well versed in the different statistical methods that will be used to analyze the data (Carsey& Harden, 2015). If the data is interpreted incorrectly the conclusions drawn from the data will be wrong. The use of these quality control measures ensure that the conclusions drawn from the data will be correct.

References:

Bryman, A., Becker, S., &Sempik, J. (2008). Quality criteria for quantitative, qualitative and mixed methods research: A view from social policy. International Journal Of Social Research Methodology: Theory & Practice, 11(4), 261-276. doi:10.1080/13645570701401644

Carsey, T. M., & Harden, J. J. (2015). Can You Repeat That Please?: Using Monte Carlo Simulation in Graduate Quantitative Research Methods Classes. Journal Of Political Science Education, 11(1), 94-107.doi:10.1080/15512169.2014.998093