Assessing and Recommending Quantitative Research Designs
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wk3assgnwellonsmquanitativeresearch.docxQUANITATIVE RESEARCH DESIGN 7
Running head: QUANITATIVE RESEARCH DESIGN
Quantitative Research Design
Monique D Brown Wellons
Walden University
Quantitative Research Design
Introduction
The determination of the most appropriate research design is a critical issue that has to consider effectively many factors linked to a particular study. The investigator has to take into account the research hypothesis, questions as well as whether the variables will be utilized. Most importantly, the difficulty of choosing the particular design is surpassed by the study characteristics. Accordingly, the purpose of this paper is to undertake a critical assessment of the strengths and weakness of research designs and subsequently recommend a quantitative design for my study alongside the rationale for the recommendation. Moreover, the paper is focused on the explanation of why some research designs are never recommended for my study. Strengths and Limitations of the research designs Experimental Design Strengths
This is the most exemplary models of research or original design. The experimental design is effective as it permits the investigator to control both exogenous variables while eliminating the extraneous variables as compared to other research designs. Moreover, this research design allows for the determination of causal relationships as it involves the manipulation of exposure to exogenous variables. Therefore, the researchers are presented with a promising opportunity to observe cause and effect as well as the influence of exogenous variable on the endogenous variable. Its effectiveness results from the fact that the controlled condition of the design permits replication for result verification. Such an element is, therefore, central to future research also to where other researchers can replicate an experiment. Therefore, experimental research design has the capability of providing the research community with a greater level of confidence in the study’s outcome. Weakness
It is not easy for the experimental design to do away with or control extraneous variables as this becomes increasingly impossible. Moreover, experimental research becomes ineffective in cases where researcher investigates real-world situations due to its inability to replicate a natural environment making the validity be at a threat. Particularly, the experimental design is also ineffective as the selection process responsible for the control of variables increasingly becomes difficult hence failing to be random. The generalization of the outcomes may prove difficult as the sample chosen when using this design may technically fail to represent the general population. Frequently, it becomes impossible, unethical to utilize random assignment in treatment as well as control cohorts. Quasi-Experimental Design (recommended) Strength
The first important strength of the quasi-experimental design is its ability to permit the investigators to examine the behaviors in the natural setting that is a tall order with the experimental design. The design uses the naturally existing samples that has an impact on the enhancement of the research validity since quasi-experiment do not depend on the utilization of random assignment when comparing different cohorts and hence it becomes increasingly important to use this design in cases where the researcher cannot control their subjects as the creation of the comparison cohorts is easy without the utilization of the random process.
Limitation
Quasi-experimental designs do not use a random selection process for assigning the subjects in various cohorts, and, therefore, the investigators must devise another technique of knowing how the non-random selection process impacts the outcomes of the study. Designs Chosen Cross-Sectional Design
The Cross-Sectional Design is not appropriate in this experiment as they are observational and uses the random sample of subjects and always link to survey research. Investigators record information gathered from the survey, but the variables would never be manipulated as well as exposed to single or multiple treatment cohorts. For instance, an investigator may use a cross-sectional design in measuring inflammation in exercisers alongside non-exercisers. The cross-sectional design provides the investigator with an effective method of examining various features concurrently and hence able to record such features of socio-economic status and age of both non-exercisers and exercisers. Instead of determining causal direction and relationships, cross-sectional research design becomes descriptive. Moreover, the variables are never manipulated in the cross-sectional research as would be in experimental research designs (Creswell, 2009). However, this research design is never appropriate in my study as it is never amenable to the research question, endogenous and exogenous variables as well as my hypothesis as the design fails to support the variables. Moreover, the hypothesis of my study is never amenable to the survey; therefore, the cross-sectional design fails to support observing how the exogenous variable impacts the endogenous variable. Also, the cross-sectional design is not effective in my study that involves cause-effect relationships since this design does not suggest such connections. Finally, since I do not have the intention of manipulating my variables but determining the effects of exogenous variables on endogenous variables, cross-sectional research design is inapplicable. Experimental Design
The main distinguishing feature between the quasi-experimental and experimental design results from the fact that experimental design is always associated with the control group where subjects are randomly assigned. Also, the experimental resign designs have their subjects exposed to treatments as plugged by the investigator while assessing the effects of such treatments. This design involves an investigation where the investigators control the effects of the exogenous variables on the endogenous variables. However, the variables that I intend to incorporate in my study can never be controlled but only observed. Moreover, I would not have an efficient study using experimental research design since the conditions prohibit random participant’s assignment. Thus, it is impossible to exert any control over the assignment of the subjects to the comparison cohorts. Based on my research question that looks at whether as well as the extent to which the participation in online-disease-specific support cohorts induces a higher sense of control over disease compared to face to face support cohort engagement amongst rare cancer diagnosed patients.
Moreover, this research design cannot help me accomplish my comparison between the two intact cohorts. This research thus is inappropriate as it will prohibit random assignment of the subjects to control as well as treatment cohorts. As the research question demands that I seek subjects with a rare cancer diagnosis, therefore, I have to assign those participants who exclusively participate in online disease-specific support cohorts to a particular group. Further, the question requires that those participants in face-to-face support cohort will also be assigned to another separate group (Frankfort-Nachmias & Nachmias, 2008). Therefore, since the participants can never be randomly assigned to a particular cohort, this justifies my choice of quasi-experimental research design. Moreover, the random assignment used in experimental design does not support the variable, participation in face-to-face support cohorts as well as online participation particularly, disease-specific support cohorts. Moreover, my hypothesis that suggests that online participation, disease-specific support cohort induces a higher sense of control over the disease as compared to face-to-face participation support cohorts particularly in patients with cancer types is never amenable to an experimental as well as a control cohort. Finally, since my study aims at measuring sense of control in participants in each cohort as and subsequently identify the endogenous variable that is efficient at inducing a sense of control in the subjects. Conclusion
The ability to choose the best research design is pegged at the research problems as well as whether such a study employs a treatment to which a particular cohort will be exposed. Moreover, choosing the research design is also embedded on the endogenous and exogenous variables together with the research hypotheses. Moreover, all individual research design has both weakness and strength that must be proactively examined and determined before settling on a particular design.
Reference
Frankfort-Nachmias, C., & Nachmias, D. (2008). Research methods in the social sciences (7th Ed.). New York: Worth. Chapter 5 Research Designs
