How will you measure the independent, dependent, and moderating variables? For some studies, it is important to identify a way to measure the change in the variables. For quantitative deductive studies non-parametric measurement instruments lead to non-parametric statistical analyses which are acceptable but not as powerful as the parametric statistical analyses. For qualitative studies the measurement might be qualitative descriptions based on the responses to the questions in an interview guide. For mixed method quasi-deductive studies the measurement plan might include both qualitative descriptions and quantitative measures (e.g., survey questions with scales, performance measures such as financial performance). The measurement plan should be consistent with the overall approach identified in the previous step and the conceptual framework and research questions. Remember - we “measure” variables and “analyze” relationships.
data collection plan
How will you collect the data using the instruments and measurement approaches identified in the measurement plan? The data collection plan includes a sampling plan. Be explicit about the nature of your population and sample, the kinds of data gathering instruments you will use, and the circumstances under which the data are likely to be gathered. Include any specific activities that you would propose to reduce bias and increase validity. The type and level of data that is collected will determine the analysis options that are available. Triangulation of sources and methods is a common technique to mitigate bias and enhance validity.
choosing a sampling approach
There are two main types of samples - probability and non-probability. The main sampling difference for each methodology (qualitative and quantitative) is based primarily on the purpose of the research. If the purpose is to deductively “test” a specific hypothesis then a random sample that is sufficiently large to represent the population is the desired sampling approach for a quantitative study. That way the findings can be generalized to that larger population. On the other end of the spectrum is an exploratory qualitative study with a purpose of “building” a theory. Qualitative inductive theory building studies worry less about representative samples and more about getting the right people to provide a rich data set - often called a “purposive” sample. Of course there are many variations to these approaches including sampling for mixed methods studies. In the end, when practical you want to work toward a representative sample but unless you are expanding the theory to increase generalizability to other populations or testing a theory a purposive sample might be more appropriate.
The need for a pilot study depends on several factors including: (a) the amount of previous experience with the survey (what steps others have taken to validate the instrument); (b) where (what participant groups) the survey have been used with; and (c) your particular situation. Read more...
Chad McAllister’s[Prospectus Version] - The population to be explored includes users who are involved in specifying requirements for IS and developers who create information systems. An opportunity sample will be used consisting of three to four companies that meet the following criteria:
- Sufficient size to create NGT groups of users and developers.
- Publicly traded company performing in the top 49% of their industry group (a measure of success determined by the stock market).
- Each company will be from a different industry to obtain a broader perspective.
- Develop a measurement plan for the variables in the research questions and hypotheses.
- Develop a data collection plan including instruments and sampling strategy.
- Support your discussion with solid peer-reviewed references and research methods texts.