For many qualitative researchers, on the other hand, the process looks more like what is outlined in Figure 16.1: The stages of data collection, data analysis, and drawing conclusions are more simultaneous and interactive (Seidman, 1991; Maxwell, 1996). The researcher begins doing analysis and drawing conclusions almost as soon as data collection begins, and the analysis and the conclusions provide direction for what additional data collection needs to occur. Unlike the positivists, for whom comparability over time is essential, many qualitative researchers see that aspect of data collection as problematic in the sense that it is a decision to be weighed given the particulars of a research project. In many cases, the advantages to be gained by adjusting and refocusing the data collection efforts as they proceed outweigh the disadvantages of changing the manner in which data are collected. One of the advantages gained when data collection and analysis overlap is theoretical sensitivity: having data collection and analysis closely guided by emerging theoretical issues (Glaser, 1978; Strauss, 1987). Now, data collection and analysis are guided by theoretical issues in all research, but in a different way. In most research, theoretical issues are used to create measuring devices before the data are collected, and what occurs during the process of data collection does not lead to changes in the measuring devices. However, because many qualitative researchers do not see a rigid separation between data collection and data analysis, this stance opens the door for the possibility of theoretical issues arising during data collection to change what kind of data is collected or from whom it is collected. So, theoretical sensitivity involves a constant interaction between theory and data collection. Data collected in one interview, for example, may raise some theoretical issues for the researcher such that later interviews are modified to collect data addressing those issues.