Reply must be at least 200-300 words. For each thread, you must support your assertions with at least 2 citations from sources such as your textbook, peer-reviewed journal articles, and the Bible. 

Field, A. P. (2018). Discovering statistics using IBM SPSS statistics (5th ed.). Los Angeles, CA: Sage.

**Leon**

Although many researchers have their preferred method of research inquiry by choosing a quantitative study or qualitative study, depending on the area of research, converting a quantitative study to a mixed study can be an arduous process requiring the researcher to include both elements of quantitative research and qualitative approaches.  Field (2018) defines a mixed design as a design which includes some independent variables that were measured using different entities and others that used repeated measures, requiring two independent variables. Essentially, combining at least one qualitative and one quantitative research component is the first step in the process of converting a quantitative study into a mixed study.  Part of the process can include utilizing both quantitative and qualitative viewpoints, collecting the data, data analysis, and inference techniques.  According to Field (2018), the mixed design process include: 1) Exploring the data, this encompasses checking for outliers, normality, etc..  This process can be conducted through box plots, histograms, and descriptive statistics;  2) Fit the model, this encompasses correcting the outliers and normality problems, using multivariate tests and multi-level model;  3) Follow-up tests, where there is either a specific hypothesis or no hypothesis, utilizing planned comparisons and post hoc tests and 4) Calculate effect sizes.  In relation to figure 16.2 and how to convert a quantitative study into a mixed study, this researcher will utilize seven strategies integral to this process.  Schooneboom & Johnson (2017) posit that there are seven major design dimensions: 1) Purpose; 2) Theoretical Drive; 3) Timing (simultaneity and dependency); 4) Point of Integration; 5) Typological versus Interactive Design; 6) Planned versus Emergent Design; and 7) Design Complexity.  Each of the dimensions of mixed methods must be thoroughly examined.  It is critical for any researcher, when considering a mixed method design to keep the issue of validity at the forefront (Shooneboom & Johnson, 2017).  

     The general process for mixed designs is the same as for any other linear model; moreover, mixed designs include both repeated measures and independent measures which essentially mandates the researcher to be concerned with homogeneity of variance and sphericity (Fields, 2018).  Utilizing a mixed method can increase the effectiveness of the research design by boosting the response rate and improving the sample composition not only in comparison with the most commonly used mix of self-administered modes, but also in comparison with unimode types (Sztabinski, 2019). 

     Utilizing a mixed design is often perceived as a complex and difficult research method.  Depending on the researcher and the topic under study, utilizing this type of method can integral to the study yielding results which are sound and valid.  Throughout any study, the validity must constantly be at the forefront of the researcher.  From a spiritual worldview, we are encouraged by the word of God.  “We have different gifts, according to the grace give to each of us” (Romans 12:6, NIV). 

References

Field, A. P.  (2018).  Discovering statistics using IBM SPSS statistics (5th ed.).  Los Angeles, CA:  Sage. 

Schoonenboom, J., & Johnson, R.  (2017).  How to construct a mixed methods research design. Kolner 

 Zeitschrift Fur Soziologie & Sozia/pschologie, 69, 107-131. 

Sztabinski, P. B.  (2019).  The use of face-to-face interviews in mixed mode design:  The problem of the achieved

     sample.  Individual & Society/Clovek a Spolocnost, 22(4), 1-28.