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Here we develop a discussion of the concept of validity in the social sciences. We first highlight the history of validity and how it has been conceptualized and measured over time. Next we discuss a type of social science data that is often overlooked in the validity measurement and assessment literature: data that are based on self-reporting. Despite the widespread use of self-reported data in various social science disciplines such as economics, political science, and sociology, there are still few reported attempts to check data accuracy. By way of giving examples, we overview self-reported data in four areas: (1) US prison population data, (2) COVID-19 case data, (3) toxic releases, and (4) fish landings. We then discuss the need for a tool and for an established workflow for assessing the accuracy and validity of quantitative self-reported data in the social sciences. We suggest that applying Benford’s law to these types of data can provide a measure of validity assessment for data that would otherwise not be assessed for accuracy; then we briefly introduce the concept of Benford validity. We conclude the chapter with a short review of existing studies that have applied Benford’s law to social science data in some manner.
Benford's Law is a probability distribution for the likelihood of the leading digit in a set of numbers. This book seeks to improve and systematize the use of Benford's Law in the social sciences to assess the validity of self-reported data. The authors first introduce a new measure of conformity to the Benford distribution that is created using permutation statistical methods and employs the concept of statistical agreement. In a switch from a typical Benford application, this book moves away from using Benford's Law to test whether the data conform to the Benford distribution, to using it to draw conclusions about the validity of the data. The concept of 'Benford validity' is developed, which indicates whether a dataset is valid based on comparisons with the Benford distribution and, in relation to this, diagnostic procedure that assesses the impact of not having Benford validity on data analysis is devised.
Mild traumatic brain injury (mTBI) is being claimed as the ‘signature’ injury of the Iraq war, and is believed to be the cause of long-term symptomatic ill health (post-concussional syndrome; PCS) in an unknown proportion of military personnel.
Method
We analysed cross-sectional data from a large, randomly selected cohort of UK military personnel deployed to Iraq (n=5869). Two markers of PCS were generated: ‘PCS symptoms’ (indicating the presence of mTBI-related symptoms: none, 1–2, 3+) and ‘PCS symptom severity’ (indicating the presence of mTBI-related symptoms at either a moderate or severe level of severity: none, 1–2, 3+).
Results
PCS symptoms and PCS symptom severity were associated with self-reported exposure to blast whilst in a combat zone. However, the same symptoms were also associated with other in-theatre exposures such as potential exposure to depleted uranium and aiding the wounded. Strong associations were apparent between having PCS symptoms and other health outcomes, in particular being a post-traumatic stress disorder or General Health Questionnaire case.
Conclusions
PCS symptoms are common and some are related to exposures such as blast injury. However, this association is not specific, and the same symptom complex is also related to numerous other risk factors and exposures. Post-deployment screening for PCS and/or mTBI in the absence of contemporaneous recording of exposure is likely to be fraught with hazards.
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