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Krause (2019)
Krause (2019)
Random chance is a mathematically elegant notion that logically is inapplicable for social science empirical research purposes. It nevertheless has been widely used to evade, rather than solve some critical problems of current social science research methodology.
Such problems must either be solved or admitted to be insoluble rather than merely statistically finessed by making unjustifiable randomness assumptions if social science is to soundly progress.
The only obvious way to achieve random sampling requires the population to be fully listed or assembled and every one of its members to be accessible for sampling, because only then could all of its members have an equal probability of being drawn in a sample from that population.
This would be a rare circumstance for many of the populations of interest to the social sciences because of there being persons who are unlocatable, unavailable, or unwilling to participate.“
Hulland et al. (2017)
Hulland et al. (2017)
When the primary aim of the research is to test the veracity of proposed theoretical effects, the use of a convenience sample may suffice.
If the goal is to test theoretical hypotheses of interest, as is usually the case, the most important consideration is to select measurement objects and a research context in which the hypotheses can be meaningfully tested, using sources of data (both primary and secondary) that yield accurate information about the units studied.
.... However, if the researcher is interested in a particular target population to which generalizations are to be made, an explicit sampling frame has to be specified and the manner in which the sample was drawn needs to be clearly and explicitly described.
Based on our review of published survey research, we classified 111 studies (55.0%) as using an explicit sampling frame, and 86 studies (42.6%) as being based on convenience samples.
In many cases we found the descriptions provided for the more complex sampling procedures to be confusing and incomplete.
..., survey researchers follow certain established survey practices ritualistically, even when they are not directly relevant to the research in question or when they are not particularly meaningful. For example, a focus on coverage, sampling, and non-response error seems misplaced when there is no real target population to which the researcher wants to generalize the findings.
However, in typical academic marketing surveys there is often no obvious target population to which the researcher wants to generalize the findings, the sample studied is arbitrary (e.g., chosen based on ease of access), and it is difficult to talk about selection bias when the sample is one of convenience (although nonresponse will lead to loss of power).
Further Readings
Further Readings
Krause, M. S. (2019). Randomness is problematic for social science research purposes. Quality & quantity, 53(3), 1495-1504. doi:10.1007/s11135-018-0824-4. Click Here.
Hulland, J., Baumgartner, H., & Smith, K. M. (2018). Marketing survey research best practices: evidence and recommendations from a review of JAMS articles. Journal of the Academy of Marketing Science, 46(1), 92-108. doi:10.1007/s11747-017-0532-y. Click Here.
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