Research design is very critical in determining the validity, reliability, and generalizability of the findings. For the research findings to be credible, they must pass statistical tests of validity, reliability, and generalizability. Since positivists support the use of empirical evidences in the criminal justice system, they apply statistical tests quantitatively to prove the credibility of the evidences. Naturalists too, have also found the application of the statistical tests in qualitative research. Therefore, whether a research is qualitative or quantitative, the statistical analysis in terms of validity, reliability, and generalization need consideration when designing the research. This essay explores the meanings of validity, reliability and generalizability and their importance in research design.
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Validity is applicable to both quantitative and qualitative research designs and interpretation in order to enhance credibility of the research findings. Golafshani argues that, “validity determines whether the research truly measures that which it was intended to measure or how truthful the research results are or whether the research instrument is specific and accurate” (2003, p. 599). Validity questions the accuracy and trustworthiness of the research findings.
For instance, validity tests the accuracy of the research design, whether between or within groups’ treatments is significant to warrant data analysis. Several processes of research such as selection of groups, treatment of groups, collection of data, data analysis, and incorporation of the confounding variables determine the validity of the findings. Inaccurate application of these research processes in the research design and process will result into invalid and incredible findings. Therefore, validity test is important in ensuring that research process is accurate in order to yield robust findings that are credible.
Reliability on the other hand is a statistical element that tests consistency of the research process and the findings. Reliability is applicable to both qualitative and quantitative research design and process. It tests consistency of the findings in terms of repeatability, stability, and periodicity of the measurements. Golafshani explains that consistency of the results “…and an accurate representation of the total population under study is referred to as reliability and if the results of a study can be reproduced under a similar methodology, then the research instrument is considered to be reliable” (2003, p.598).
The reliability of the methodology or research instrument depends on the ability to give consistent results no matter the kind of data, time, and place of the research. Though initial reliability test may prove to have consistent results, researchers should not assume its consistency over a long period since research instrument wear out and the research methodology is prone to additional external influences. Reliability test is very important in research design and analysis of the data in order to minimize reliability errors associated with the research process.
For the research findings to be credible, they should draw upon the theoretical rationale of generalization. Generalization involves extrapolation of the reliable and valid research findings to the entire population or other variables. In this case, generalizability tests the extent of extrapolating the research findings to the entire population. Golafshani (2003) posits, “The generalization of the findings to wider groups and circumstances is one of the most common tests of validity for quantitative research” (p.603).
The generalizability tests external validity of the findings hence their applications. Proper research design and process will enhance generalizability of the results making them transferable to wider population. Therefore, the three concepts of research design; validity, reliability and generalizability, are very important in ensuring the credibility and relevance of the research findings.
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Golafshani, N. (2003). Understanding Reliability and Validity in Qualitative Research. The Qualitative Report, 8(4), 597-607.