Estimating the Standard Deviation From the Range: a Replication of Analysis of Demographic Data Reported in <i>Marriage &amp; Family Review</i>, 2016-2017

Schumm, Walter R.; Crawford, Duane W.; Higgins, Michael J.; Lockett, Lorenza; Al‐Rashed, Abdullah A.A.A.; Ateeq, Asma bin

doi:10.1080/01494929.2018.1500128

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2019

2024

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“…We noted that standard deviations for binary variables in large samples should seldom exceed 0.55, so if an article reported a standard deviation of 0.71, it would have to be an error, either a typographical error or possibly falsified data. We included a formula for predicting the standard deviation from the mean, for binary variables (e.g., 0 and 1 being the only possible values) [6].…”

Section: Introductionmentioning

confidence: 99%

Patterns of Means and Standard Deviations with Binary Variables: A Key to Detecting Fraudulent Research

Schumm¹,

Crawford

Lockett

2019

BJSTR

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Heathers and his colleagues have proposed a variety of tests to detect inconsistencies in research data, including the GRIM, SPRITE, DEBIT, and RIVETS tests. Binary data are common in social science research, for such variables as male/female, rural/urban, white/nonwhite, or college educated/not college educated. However, the standard deviation for binary data is a direct mathematical function of the mean score. We show how standard deviations vary as a function of the mean and how the maximum possible standard deviation varies as a function of sample size for a mean of .50. Implications for detecting fraudulent data are discussed.

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Section: Introductionmentioning

confidence: 99%