Search results
Results From The WOW.Com Content Network
Statistics, when used in a misleading fashion, can trick the casual observer into believing something other than what the data shows. That is, a misuse of statistics occurs when a statistical argument asserts a falsehood. In some cases, the misuse may be accidental. In others, it is purposeful and for the gain of the perpetrator.
Medical data, including patients' identity information, health status, disease diagnosis and treatment, and biogenetic information, not only involve patients' privacy but also have a special sensitivity and important value, which may bring physical and mental distress and property loss to patients and even negatively affect social stability and national security once leaked.
Pages in category "Misuse of statistics" The following 27 pages are in this category, out of 27 total. This list may not reflect recent changes. ...
Data dredging (also known as data snooping or p-hacking) [1] [a] is the misuse of data analysis to find patterns in data that can be presented as statistically significant, thus dramatically increasing and understating the risk of false positives.
A Lancet review on Handling of Scientific Misconduct in Scandinavian countries gave examples of policy definitions. In Denmark, scientific misconduct is defined as "intention[al] negligence leading to fabrication of the scientific message or a false credit or emphasis given to a scientist", and in Sweden as "intention[al] distortion of the ...
Based on self-report by staff the prevalence of elder abuse in institutional settings such as nursing homes is 64.2%. The prevalence of psychological abuse is 33.4%, physical abuse 14.1%, neglect 11.6%, and sexual abuse 1.9%. Risk factors for abuse were being female, cognitive impairment, and being older than 74. [10]
Unwarranted variation in medical practice is costly and deadly as noted by Martin Sipkoff in 9 Ways To Reduce Unwarranted Variation.Analysis of Medicare data revealed that per-capita spending per enrollee in Miami was almost 2.5 times as much as in Minneapolis, even after adjusting data for age, sex, and race.
For example, the sharing of healthcare data can shed light on the causes of diseases, the effects of treatments, an can allow for tailored analyses based on individuals' needs. [12] This is of ethical significance in the big data ethics field because while many value privacy, the affordances of data sharing are also quite valuable, although ...