When reported accurately, non-experimental research has a major impact because it can be applied to perform research when experimenting is not desirable or feasible. Non-experimental research designs are employed by researchers when they seek to comprehend an issue fully without constricting it by factors. They also utilize this type of design when they do not have a specific cause-effect study problem in mind and often analyze the natural events as they transpire.
Non-experimental designs have their strengths, notably lower costs in many instances where research calls for a swift survey or when the number of variables involved in the study must be kept to a bare minimum. Another advantage is that it can be utilized to examine many unique phenomena and analyze historical events (Mattei et al., 2020). Non-experimental designs operate remarkably well, whether striving to safeguard the natural behaviors of a population or retaining their self-possession and integrity with a non-invasive technique.
There are weaknesses associated with non-experimental designs, such as their concise nature as a result of not allow for the gathering of data post-treatment. The quick, grab-and-go nature of non-experimental quantitative designs cannot deliver the same in-depth results as experimental designs. Non-experimental designs often fail to produce adequate data from which researchers may draw complicated, revealing, or truly valuable conclusions (Podsakoff & Podsakoff, 2019). Non-experimental designs also have drawbacks, such as their compact nature, because they restrict the data collection after treatment. Non-experimental quantitative designs cannot generate the same in-depth results as experimental design due to their grab-and-go aspect.
Non-experimental research takes place during a study whenever the researcher is unable to direct, manage, or alter the subjects and instead must draw a conclusion from analysis or observations. This means that the methodology cannot show an actual cause and effect connection and cannot rely on correlations, surveys, or case studies. Overall, non-experimental research generally uses informative or comparative methods without the researcher adopting any overt alterations by stating the facts as they are or explaining how one variable is related to another.
References
Mattei, A., De Stavola, B. L., & Mealli, F. (2020). Preface to the papers on ‘causal inference from non‐experimental studies: Challenges, developments and applications.’ Journal of the Royal Statistical Society: Series A (Statistics in Society), 183(4), 1329–1332.
Podsakoff, P. M., & Podsakoff, N. P. (2019). Experimental designs in management and leadership research: Strengths, limitations, and recommendations for improving publishability. The Leadership Quarterly, 30(1), 11–33.