Triangulation design validating quantitative data model dating tips for women third date
The most common and well-known approach to mixed methods research continues to be triangulation design. Quantitative data can support qualitative research components by identifying representative patients or outlying cases, while qualitative data can shed light on quantitative components by helping with development of the conceptual model or instrument.During data collection, quantitative data can provide baseline information to help researchers select patients to interview, while qualitative data can help researchers understand the barriers and facilitators to patient recruitment and retention.Lastly, the fourth situation is when the quantitative results are difficult to interpret, and qualitative data can assist with understanding the results (Creswell & Plano Clark, 2007).The purpose of this article is to illustrate mixed methods methodology by using examples of research into the chronic pain management experience among American Indians.In the late 1970s, the term “triangulation” began to enter methodology conversations.Triangulation was identified as a combination of methodologies in the study of the same phenomenon to decrease the bias inherent in using one particular method (Morse, 1991).Simultaneous sequencing is postulated to be simultaneous use of qualitative and quantitative methods, where there is limited interaction between the two sources of data during data collection, but the data obtained is used in the data interpretation stage to support each method's findings and to reach a final understanding.Sequential sequencing is postulated to be the use of one method before the other, as when the results of one method are necessary for planning the next method.
Mixed methods research combines elements of qualitative and quantitative research approaches for the broad purpose of increasing the breadth and depth of understanding.The results of the separate level analyses will be compared, contrasted, and blended leading to an overall interpretation of results. Thus, at level 1, quantitative administrative data sets representing health care received by American Indians, both across the United States and in broad regions, will be used to evaluate macro-level trends in utilization of health care and in basic outcomes, such as opioid-related deaths.At level 2, more detailed quantitative Washington state tribal clinic data will be used to identify American Indian populations, evaluate breakdowns in the delivery of care, and identify processes that lead to unsuccessful outcomes.During data analysis, qualitative data can assist with interpreting, clarifying, describing, and validating quantitative results.Four broad types of research situations have been reported as benefiting particularly from mixed methods research.