Research Paper on Exploring Relationship between External & Internal Validity in Research Designs

Introduction

Throughout the field of research, several aspects are always put into consideration. It is still essential to be careful with the way each experimental issue is handled. It is, therefore, the interest of this paper to explain the relationship between external and internal validity factors in research designs. Furthermore, the weaknesses and strengths of various experimental models will be described in this paper. Lastly, it is with the best interest that a summary of two pieces of research conducted within the last ten years be made. Therefore, this paper will summarize two articles of study and give equal standing.

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Internal and External Variable-Related Validity

There is a difference between the internal and external validity of variables. Internal validity explains the process of experimenting. It details whether or not the procedure avoids confounding, a situation where one or more variables are acting at the same time. According to Mullinix et al. (2015), lower levels of confounding are achieved when we have higher levels of internal validity. The best way to explain internal validity, therefore, is checking the road a piece of research allows you to define various views. External validity is the way theories and data determine one setting or another.

The production of neighborhood policing systems or problem-oriented policing operations is an example of internal validity. Police departments use these policies to organize and structure communities in troubled systems to gain trust and come up with methods of solving the crimes. An excellent example of external validity is the way people assume that increased police patrols or police presence in particular stations or areas directly reduced crime rates. While this might sound true in localized areas, it may not hold the truth in regions with different sub-areas within a large community that is compounded with many problems daily. Therefore, there is a big difference between internal and external validity. In research, the differences come out more clearly than when written in literature.

In research, internal validity plays a significant role. It makes it easy for inferences to be made in a more accurate way about the study. Several factors affect the internal validity of data in quantitative research designs. One of the factors is the type of adopted research design or method. The available research designs include experimental research, descriptive research, relationship-based research, or quasi research (Campbell & Stanley, 2015). Another factor that affects the validity of data is the potential threats to internal validity. Eight factors have been identified to pose a significant threat to the validity of data. They include testing, research Reactivity, History, Attrition, Maturation, Selection Bias, Instrumentation, and Statistical Regression (Mullinix et al., 2015). According to Hagen (2014), history emphasizes on whether incidences occurred during experiments that had effects on the dependent variables. Maturation places value on finding out whether the changes in the dependent variables took place owing to the usual focus as a time function - the third aspect, which is testing delves on finding out whether pretest results affect posttest results. Instrumentation measures the difference that was created when the dependent variable was measured during an investigation Borusyak, Hull & Jaravel, 2018). Research reactivity entails focusing on the observed topics. Statistical regression involves checking the tendency of the outcomes of tendency subjects towards the mean on recurring tests. Selection bias bases on individual selection and collection, while attrition focuses on the discrepancy of forfeiture regarding contributors across groups (Hagen, 2014).

External validity refers to the soundness of severe implications in researches based on an investigation on tests to determine their validity. It refers to the extent to which investigation results can be generalized to individuals and circumstances. The importance of external validity lies in the fact that causal relationships can be widespread to various people, trials, periods, and surroundings. However, there is a threat to external validity, and this is determining how an individual result can be incorrect in developing simplification.

Strengths and Limitations of Experimental Research Designs

There are several strengths and limitations of experimental research designs. An emphasis is put into place for innovative research on associations amongst identified variables. This study also offers substantial unintentional interpretational evidence. There are three critical elements of the experimental study design, which are: Equivalence, pretest and posttests, and innovative and control groups (Hagen, 2014). First, the equivalence which refers to the attempt to select and assign subjects to experimental and control groups in such a manner that they are as similar as possible (Hagen, 2014).

What is more, easy determination of cause and effect relationship center focuses on deploying independent variables to regulate the causal relationship effortlessly. Last, of all, better results can be accomplished due to the experiment being set up with stringent circumstances. Tests can be repeated, and results can always be rechecked if the data is not comprehensive the first time. The disadvantages of experimental research include failure to experiment, creating artificial situations, and subject to human error (Borusyak, Hull & Jaravel, 2018). An inability to test is when one is interested in a study but is not very capable of manipulating the variables. Besides, creating artificial situations involves insignificant variables, which results in simulated conditions. Last but not least, subject to human error results in all research; consequently, results become inaccurate.

Contemporary Examples

Crime media and pop culture are two examples of experimental research conducted recently. In such studies, experimentation is exceptional since it only exists to produce interconnections. This is because the first plan of the investigation is making investigators control the environment, atmosphere, and variables under investigation. In these studies, experiments suffered great difficulties/ the controls and precision usually applied in operations prove a barrier to implementing the research outcomes in real-life situations. In criminal justice systems, the aftermath of such findings makes it hard to get results on the social construction of penal systems in social ways and our response to the image of criminality and appropriate criminal justice.

Conclusion

This paper has explored the external and internal validity variables, their importance and disadvantages. The study has also indicated the factors that affect the effectiveness of internal and external validity variables. Experimental designs have their strengths and weaknesses. Connections between experiments are very significant in any innovative design, as seen in this paper. This paper has summarized two recent pieces of research within the criminal justice system conducted within the last ten years.

References

Borusyak, K., Hull, P., & Jaravel, X. (2018). Quasi-experimental shift-share research designs (No. w24997). National Bureau of Economic Research.

Campbell, D. T., & Stanley, J. C. (2015). Experimental and quasi-experimental designs for research. Ravenio Books.

Hagen, F. (2014). Research Methods in Criminal Justice and Criminology (9th ed.). Upper Saddle River, NJ: Pearson.

Mullinix, K. J., Leeper, T. J., Druckman, J. N., & Freese, J. (2015). The generalizability of survey experiments. Journal of Experimental Political Science, 2(2), 109-138.