Exploring the Logic of Experimental Design

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Introduction
“Maximin design maximizes either the minimum efficiency, or the minimum relative efficiency of the design relative to the optimal design, over a range of plausible parameter values, by choosing the design with the highest minimum” (van Breukelen, 2013, p. 154).
A project worthy of research requires a logical design with strongly articulated elements, appropriate representative populations, and implemented controls to produce conclusive results to support theories, hypothesis, and the proposed research questions. Components of a research study can make a perfectly design research project fail based on validity, confounds, and faulty causal-relationships conveyed as proper correlations. These aspects are at the root of debates on the legitimacy of qualitative research and the coherence of logic in standard research designs (Maxwell, 1992; 1998).
In this paper, the discussions focus on the purpose, advantages, and disadvantages of conducting experimental designs, importance of internal and external validity claims, define what is/are control, control groups, confound, cause, and how correlation and causation are related. Finally, concluding with specific questions identified for this assignment.
Purpose of conducting an experiment
Researcher use experiments to predict whether a cause and effect relationships exist between variables of interests in cognation of discovering new, or confirming established phenomena, and communicating such knowledge of experimental work for acceptance by the relative community (Hart, Mulhall, Berry, Loughran, & Gunstone, 2000; Jackson, 2012). Experimental designs support a unique distinctions based the designs efficiencies to manipulate control over variables of interest and predict a...

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...SAGE Publications, Inc. doi: http://dx.doi.org.proxy1.ncu.edu/10.4135/9781412961288.n77
Roe, B. E., & Just, D. R. (2009). Internal and external validity in economics research:
Tradeoffs between experiments, field experiments, natural experiments, and field data. American Journal of Agricultural Economics, 91(5), 1266-1271. doi:10.1111/j.1467-8276.2009.01295.x
Teunissen, C., Menge, T., Altintas, A., Alvarez-Cermeño, J., Bertolotto, A., Berven, F., &...
Bartos, A. (2013). Consensus definitions and application guidelines for control groups in cerebrospinal fluid biomarker studies in multiple sclerosis. Multiple Sclerosis (Basingstoke, England), 19(13), 1802-1809. doi:10.1177/1352458513488232 van Breukelen, G. P. (2013). Optimal experimental design with nesting of persons in organizations. Zeitschrift Für Psychologie, 221(3), 145-159. doi:10.1027/2151-2604/a000143

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