Qualitative Data Analysis in Evaluation a Federal Agency Program

Rogers (2010) chapter on qualitative analysis described many useful and practical methods to help use this tool effectively and efficiently. The purpose of this essay is to examine this book chapter and address the important and key issues that are presented in the literature. This essay will also provide practical examples of the information presented in this argument from federal agencies to help contextualize the information and to demonstrate the practicality of its methods at a governmental level.

Rogers proposed a complex systematic framework for analyzing qualitative data for evaluation in this chapter. He created the mnemonic PPOIISED to help guide this process. He stated that this mnemonic " is intended to remind users of three different meanings of the word poised in that good qualitative data analysis finds an appropriate balance between compteting imperatives, uses strategies that are focused on action, and has a sense of assurance based on a systematic approach and considered choices " (p.430).

PPOIISED stands for triggers for important questions that the researcher needs to be asking to validate the data. The following trigger words are used to help the researcher remember the method: -Purposes -Paradigms -Options -Interpretations -Iterations -Standards -Ethics -Displays Each one of these ideas provides a pillar for the framework of solid quantitative data analysis. The remainder of the chapter goes into great detail explaining each one of these principles and how they can contribute to a method of analysis. Purposes: This keyword holds the most importance in the system.

Researchers need to have a clear and definable purpose before beginning any type of analysis. The quality of information must be viewed through a purposeful lens in order to give it meaning. Paradigms: It appears that research has transcended a bipolar paradigm where either all data was entirely qualitative or quantitative. Today's approach is much more of a hybrid. Paradigms are larger pictures in which the data must be viewed in order to hold any relevance. Federal agencies tend to resort back to the days of bipolarity.

This is however inherent within governmental institutions where the idea of governance is bipolar in nature. The two poles consist of the government and the governed where, the government assumes a position of divine righteousness and infallibility within its edicts. Options: Creativity is very important when doing research. The many options that govern any research question can be very helpful in opening up new avenues of discussion. On the other hand options appear to present an unlimited or unsolvable problem when taken in serious consideration.

Interpretations: According to Rogers "interpretation refers to making meaning out of the data in terms of understanding discrete pieces of data, categorizing the data, and identifying overall patterns. This key term is essentially quantifying qualitative information. It insists that relativeness is important but impossible without having some boundaries and restrictions. The author discusses various forms of coding to help in this process. Federal agencies tend to interpret their data from an insistent point-of-view.

Mortality rates presented from research of federal institutions are coded to infer that death is generally a bad thing while ignoring some of the positive aspects of death. Iterations: Iterations help define qualitative data by spinning them around and rerunning data to determine new and useful relationships. Essentially to iterate qualitative data means to cycle it. Federal agencies such as the IRS iterate their tax code every year to produce what they believe to be a fair standard, reflective of the status quo.

Standards: It is important to remember when analyzing qualitative data that standards are used to help guide what is acceptable or not within a research project. Standards are reflections of the paradigm in which the data is being analyzed and may vary between differing paradigms. Ethics: This idea is straightforward. Ethics are important no matter what type of analysis is.