MMPA 6910: Threats and Ethics in Quantitative Research Discussion

This discussion post delves into the complexities of quantitative research, focusing on the threats to both internal and external validity. The author meticulously outlines various threats, including selection bias, statistical regression, and testing effects, providing clear explanations of how these factors can undermine the reliability and generalizability of research findings. Furthermore, the post offers practical strategies for mitigating these threats, such as employing well-defined inclusion criteria, utilizing statistical adjustments, and implementing random selection. The discussion also addresses the ethical considerations inherent in quantitative research, emphasizing the importance of confidentiality, honesty, objectivity, and respect for intellectual property. The author underscores that adhering to these ethical principles is crucial for maintaining the credibility and trustworthiness of research. The post concludes by acknowledging and agreeing with a classmate's insights, reinforcing the critical points about validity threats and ethical standards in research, and referencing the work of other researchers and academics.

Running head: DISCUSSION 1
Discussion: Designing Quantitative Research
Name
Institution

DISCUSSION 2
Discussion: Designing Quantitative Research
Threats to Internal and External Validity in a Quantitative Research
Internal validity refers to the rigor and the magnitude to which the research evidence
supports the cause-effect of the study. Internal validity is important in a quantitative research.
However, it might be compromised by certain threats that include selection threat. Selection is
one of the threats that have massive impacts on research. Selection occurs when there is a bias in
the choosing of the participants. Statistical regression threat stems from the inefficiencies in the
measurement of the dependent variables (Halperin, Pyne & Martin, 2015).
External validity is the extent to which the research generate the findings that can be
generalized. Generalization is the process in which the research findings can be applied to a
totally different setting in which the study was not conducted. The more generalizable the
findings are, the more external valid it is. Just like internal validity, external validity can be
compromised by certain threats. Such threats include the interaction effects of selection biases,
interaction effect of testing, multiple-treatment interference, and multiple-treatment interference
(Campbell, 2017). Interaction effects of selection biases happen when there is no uniformity in
the choice of selection factors in the participants. Interaction effect of testing threats occurs if
there is interference from the interactions between the experimental and pre-testing groups in the
study (Campbell, 2017). On the other hand, multiple-treatment interference threats stem from
there are inefficiencies in the amount of treatments that different categories of participants get
during the study. Finally, the reactive effects of experimental arrangements are attributed to the
influences of perception of the participants towards the research especially after getting a prior
knowledge of the study.

DISCUSSION 3
How to deal with the Threats to Internal and External Validity in a Quantitative Research
The researcher must eliminate the threats because they can compromise the validity and
reliability of the study. Hence, to tackle the threats to external validity, the researcher should take
a number of steps including the use of a well-defined inclusion and exclusion criteria for all the
participants; use of statistical methods in the adjustments of the study; application of the out-of-
laboratory field experiments; replication of the study in a different setting; and the use of
psychological realism-preventing the participants from knowing the real aims and objectives of
the study (Walliman, 2017). Meanwhile, to deal with the threats to internal validity, the
researcher should adhere to a specified study protocol, use of experimental manipulation;
blinding of the participants; random selection of the participants; and a systematic
randomization-a random allocation of the individual participants to take part in the study as the
members of the control and treatment groups (Babbie, 2017). These are the strategies that should
be applied when preventing the threats that might interfere with the internal and external validity
of a research.
Ethical Issues in Quantitative Research
Ethics is a standard code of principles that govern the conduct of individuals. Ethics is
universal because it is applied everywhere-research, business, religion, school, name it! In
quantitative research, there are certain ethical issues that must be put into consideration. These
include confidentiality, honesty, objectivity, safety, and respect to intellectual property rights
(Burkholder, Cox & Crawford, 2016). Failure to adhere to these ethical principles can be
undesirable because it compromizes the validity, reliability, and credibility of the research.
When designing the quantitative research, the researcher must consider these ethical
principles. They matter a lot and can dictate how the research design is to be done. For instance,

DISCUSSION 4
in order to guarantee confidentiality, the researcher must apply the principle of anonymity. To be
objective, the researcher must be focused and stick to integrity, fairness, and equality. When
selecting the participants, the researcher should not display any form of biasness. Instead, a
sampling technique that enhances fairness and gives all participants equal chances of
participation must be adopted (Kornfeld & Titus, 2017). A strict compliance with such ethical
standards can make the research credible, valid, reliable, and trustworthy. At no one time should
the researcher ignore these ethical principles. They were developed and recommended for a
research because of the important contributions that they make.
Responses to Classmates’ Posts
Jaunell Latty-Miller, I would like to commend you for your discussion. I agree with all
the points you say about the threats to internal and external validity. You give a precise, accurate,
and detailed explanation on each of the threats and how to address them. For example, you say
that internal validity might be compromised by many threats including history, instrumentation,
and testing threats. You are right for saying that testing threat is associated with the any pre-test
that alters the understanding and perception of the participants. Meanwhile, instrumentation
threat is caused by the ineffective measurement of the dependent variables. I also agree with the
points you express regarding the ethical standards in research. The concept of confidentiality and
voluntary participation are right. I fully-agree with you.

DISCUSSION 5
References
Babbie, E. (2017). Basics of social research (7th Ed.). Boston, MA: Cengage Learning.
Burkholder, G. J., Cox, K. A., & Crawford, L. M. (2016). The scholar-practitioner’s guide to
research design. Baltimore, MD: Laureate Publishing.
Campbell, D. T. (2017). Factors relevant to the validity of experiments in social settings. In
Sociological Methods (pp. 243-263). New York: Routledge.
Halperin, I., Pyne, D. B., & Martin, D. T. (2015). Threats to internal validity in exercise science:
a review of overlooked confounding variables. International Journal of Sports
Physiology & Performance, 10(7), 141-153.
Kornfeld, D. S., & Titus, S. L. (2017). Ethics: More research won't crack misconduct. Nature,
548(7665), 31.
Walliman, N. (2017). Research methods: The basics. New York: Routledge.