Mixed Research Methods - Case Study Example

Introduction Mixed research methods have been referred to by a variety of s such intergrated, mixed methodology research or hybrid. The foundation of using these techniques varied in great extends but generally depicted the scope of research offset the weaknesses involved. The potentials of mixed method designs have been distinguished by the degree of data over the other, grouping various sources of data, time taken in collecting data (qualitative and quantative) is it successively or concurrently. This discussion endeavors to discuss choosing mixed method designs in forensic science and types of mixed data design, David et al (2007). Mixed method techniques are procedures for gathering, evaluating, reporting and interpreting data. They depict different models for conducting research as they guide researchers in their investigation and come up with conclusions or recommendations. After which the research has to choose which the appropriate design that suits the study. This is essential because the researchers have to be well conversant with the mixed design techniques. Of great importance when selecting a mixed research design is to know the purpose, procedure strengths and challenges of each technique. Researchers also need to conversant with timing, combining decisions from the various types of nixed method design and weighting because they are some of the aspects that determine the suitability of a good design, Creswell, et al. (2003). Timing Also called implementation is the short-term relation between qualitative and quantative techniques when conducting a research. In short, timing is concerned with the analysis and interpretation of data and statistics. In mixed method design timing can either be simultaneous or chronological. Simultaneous timing occurs in one phase where the researcher accomplishes qualitative and quantitative data respectively, whereas chronologically, the study collects the two data in different phases; that is, the researcher opt to start with collecting, analyzing and interpreting qualitative data then quantitative or vice versa, Creswell, et al. (2003). Weighting Weighting in mixed method designs is an important approach for both qualitative and quantitative techniques. An investigator has to choose between the two data and decide on which to prioritize. Weighting options: quantitative or qualitative and qualitative or quantitative. Quantitative method has been a global study option and a realistic global inspection is impartiality between the two techniques with emphasis on research. Mixing This is the precise relation between qualitative and quantitative data. A research study that entails the two data without clearly mixing them is basically a collection of various techniques. An accurate and a suitable mixed method design attempts to decide on how to combine the two data. Mixing qualitative and quantative data can be embedded, merged or connected, Morgan, L. (1998). Types of mixed methods design. The major types of mixed methods designs are; triangulation design, embedded design explanatory and exploratory design. Triangulation Design This design deals with getting diverse but corresponding data on the same topic that purposes to combine and contrast the strengths and weaknesses of quantative and qualitative techniques. The procedure involved in triangulation design involves one phase design where the researcher executes qualitative and quantitative techniques at the same time and with the same weights. Naturally, the researcher combines data from quantitative and qualitative methods during the analysis for easy interpretation. This design is suitable for studying alcohol and drug addiction among the teenagers in rural areas. Because it makes insightful sense as it forms a platform for opinions about other types of mixed method designs and, it is efficient as both qualitative and quantitative data are collected in one phase at the same time. In addition, qualitative and quantitative data can be collected singly and data analyzed separately as long as the research team has both professionals in qualitative and quantitative data collection, Creswell et al., (2003). Challenges and solutions A lot of professional experts are required because sequential data collection and equal weights. This can be solved by having a research team that has expertise in both qualitative and quantitative techniques alternatively training the available researchers in both methods. Researchers are likely to face risks involving difficulties in merging qualitative and quantitative data in instances where data is not same .These can be addressed by collecting more data to come with compatible one, Creswell, et al. (2003). The Embedded Design Involves one type of data providing a minor function in a study that focuses on primary research techniques on another kind of data and it can either be one phase or two face designs. Used by researchers to choose between qualitative or quantitative methods such as developing a treatment, study the course of intervention like incidence of depression diabetes among Africa America or mechanisms that share variables. Procedure for embedded design; involves the combination of different data with one data type being entrenched within a design structured from another type of data. For example, embedding quantitative data within qualitative methods. This type of mixed design is good because it can be used by researchers who do not have time or enough resources to collect both qualitative and quantative information since one type of data is important than the other. Can also be done by anyone who has a rough idea about research and lastly, it appeals to more financial support as the main goal is to get quantitative data as an experimental or correlation analysis, Morgan, L. (1998). Challenges and solutions It’s normally hard to merge outcome when two types of data are used to solve different analysis under study. Unlike the triangulation design, embedded design aims at separating results from the two data. There is also inadequate information embedded on design because few researchers have studied it. This can be addressed by researcher using quantative information on large scale in qualitative data, Morgan, L. (1998). The Explanatory Design This is a two phase design. It aims at using qualitative data to assist in describing the outcomes in quantative data. Appropriate when the researcher want to use quantitative interviewer features to steer decisive illustration for a qualitative phase. Explanatory procedure involves conducting and studying of quantitative information, followed by gathering qualitative data to design for a purposeful sampling from quantitative information. Since it starts with collecting and analyzing quantitative data researchers prioritize quantitative data than qualitative one. By virtue of the fact, that it is a two phase design, there is an opportunity of easy implementation of the analysis because the researcher gathers data in separate phases and also at different times. Possibly it can be one by one researcher. It’s mostly preferred by quantative researchers because it generally begins with a strong quantitative course. In addition the final report can be in two phases providing a clear description of the research to the readers, Morgan, L. (1998). Challenges and solutions It is time consuming in the execution of the two phases, therefore, need for researchers to limit the time by reducing the number of participants and decide if it is appropriate to use the same individuals for both phases to save on time. It is cumbersome to get approval from the internal review board since the researchers cannot tell how to participants are chosen in the phase two because initial outcomes have to provided first. This can be addressed by using the same participants from the same population in all the two phases, Morgan, L. (1998). The Exploratory Design This design is based on the idea that explorations are essential in a study in cases where there are no measures or equipments, there are unknown variables and there are no laid down procedures. This design is significant in the identification of essential unknown variables using quantitative data, when generalizing findings in various groups or detailed investigation of an incident and assesses its dominance, Creswell et al., (2003). Just like explanatory design, exploratory design is a two phase technique. It begins with qualitative information, to discover an incident then quantitative data to support findings in the initial study as a result a lot of emphasis are stressed on the qualitative information. The use of separate phases in this design ensures clear description of the final report, furthermore, the combination of both qualitative and quantative makes this design acceptable quantative audiences and it is straightforwardly used in multiphase research and single studies, David et al (2007). Challenges and solutions It is time consuming and tiring and therefore important to include time management in the study plan budget. Mixed method designs can provide realistic beneficial when exploring complex studies. The qualitative information creates awareness of results and the statistical data will offer a detailed analysis of the study. However, mixing qualitative and quantitative methods is cumbersome, time consuming and costly, Creswell, et al. (2003). References David et al (2007), Merging Qualitative and Quantitative Data in Mixed Methods Vol. 3, Oxford University press;Oxyford. Creswell, et al. (2003). Advanced mixed methods research designs. In A. Tashakkori & C. Teddlie (Eds.), Handbook of mixed methods in social and behavioral research (pp. 209–240). Thousand Oaks, CA: Sage. Morgan, L. (1998). Practical strategies for combining qualitative and quantitative methods: Applications to health research. Qualitative Health Research, 8(3), 362–376. Read More