Experimental Design and Quasi- Experimental Design
Experimental Design and Quasi- Experimental Design
Cherry Spelock
Ohio University
An experimental study is defined by the way a researcher manipulates independent variables to prove or disprove a hypothesis. Outcomes are then measured and recorded. Experimental studies are considered one of the most valid ways of determining causal relationships (Byiers, Reichle, & Symons, 2012). When the independent variable cannot be controlled or other factors important to the study are out of the researchers control, the study is then called a Quasi- Experimental design study ( Polit, & Chaboyer, 2012).. The purpose of this paper is to identify the differences between the two types of studies, list several strengths and weaknesses of each study and to determine whether the sample research study from class readings is an Experimental design study or a Quasi- Experimental design study. Similarities between the two designs are the use of participants or subjects who agree to submit to some form of treatment or review, data is gathered from the participants and measured to see if the treatment or testing was the cause of any changes in results. Differences between the two forms of research is that in a Quasi- Experimental study participant are not necessarily chosen at random as would be in an Experimental study. The control group and the treatment group in a Quasi –Experimental study may not undergo the exact same parameters of treatment. When this occurs, different types of hypotheses may develop, questioning the validity of the findings. For instance, if a researcher wanted to study the effects of a certain cancer drug and was able to randomly select a control group, a treatment group and isolate and control the independent variable, an Experimental study would be ideal. On the other hand if a research wanted to conduct a study on the effects of proper nutrition and cancer, a quasi-Experimental study might be the better route to follow due to the lack
Cherry Spelock
Ohio University
An experimental study is defined by the way a researcher manipulates independent variables to prove or disprove a hypothesis. Outcomes are then measured and recorded. Experimental studies are considered one of the most valid ways of determining causal relationships (Byiers, Reichle, & Symons, 2012). When the independent variable cannot be controlled or other factors important to the study are out of the researchers control, the study is then called a Quasi- Experimental design study ( Polit, & Chaboyer, 2012).. The purpose of this paper is to identify the differences between the two types of studies, list several strengths and weaknesses of each study and to determine whether the sample research study from class readings is an Experimental design study or a Quasi- Experimental design study. Similarities between the two designs are the use of participants or subjects who agree to submit to some form of treatment or review, data is gathered from the participants and measured to see if the treatment or testing was the cause of any changes in results. Differences between the two forms of research is that in a Quasi- Experimental study participant are not necessarily chosen at random as would be in an Experimental study. The control group and the treatment group in a Quasi –Experimental study may not undergo the exact same parameters of treatment. When this occurs, different types of hypotheses may develop, questioning the validity of the findings. For instance, if a researcher wanted to study the effects of a certain cancer drug and was able to randomly select a control group, a treatment group and isolate and control the independent variable, an Experimental study would be ideal. On the other hand if a research wanted to conduct a study on the effects of proper nutrition and cancer, a quasi-Experimental study might be the better route to follow due to the lack
References: Byiers, B. J., Reichle, J., & Symons, F. J. (2012). Single-Subject Experimental Design for Evidence-Based Practice. American Journal of Speech-Language Pathology, 21(4), 397-414. doi:10.1044/1058-0360(2012/11-0036) Polit, D., & Chaboyer, W. (2012). Statistical process control in nursing research. Research In Nursing & Health, 35(1), 82-93. doi:10.1002/nur.20467