title: The Effect of Random Error on Diagnostic Accuracy Illustrated with the Anthropometric Diagnosis of Malnutrition.
abstract: BACKGROUND
  It is often thought that random measurement error has a minor effect upon the results of an epidemiological survey. Theoretically, errors of measurement should always increase the spread of a distribution. Defining an illness by having a measurement outside an established healthy range will lead to an inflated prevalence of that condition if there are measurement errors.
  
  
  RESULTS
  A Monte Carlo simulation was conducted of anthropometric assessment of children with malnutrition. Random errors of increasing magnitude were imposed upon the populations and showed that there was an increase in the standard deviation with each of the errors that became exponentially greater with the magnitude of the error. The potential magnitude of the resulting error of reported prevalence of malnutrition were compared with published international data and found to be of sufficient magnitude to make a number of surveys and the numerous reports and analyses that used these data unreliable.
  
  
  CONCLUSIONS
  The effect of random error in public health surveys and the data upon which diagnostic cut-off points are derived to define "health" has been underestimated. Even quite modest random errors can more than double the reported prevalence of conditions such as malnutrition. Increasing sample size does not address this problem, and may even result in less accurate estimates. More attention needs to be paid to the selection, calibration and maintenance of instruments, measurer selection, training & supervision, routine estimation of the likely magnitude of errors using standardization tests, use of statistical likelihood of error to exclude data from analysis and full reporting of these procedures in order to judge the reliability of survey reports.
authors.affiliation: Research Center Health Policy and Systems - International Health, School of Public Health, Université Libre de Bruxelles, Brussels, Belgium.
authors.forename: Emmanuel
authors.initials: E
authors.lastname: Grellety
authors.affiliation: Department of Medicine and Therapeutics, University of Aberdeen, Aberdeen, Scotland.
authors.forename: Michael H
authors.initials: MH
authors.lastname: Golden
mesh_terms: D000704:Analysis of Variance; D000886:Anthropometry; D002675:Child, Preschool; D003627:Data Interpretation, Statistical; D003951:Diagnostic Errors / Q000517:prevention & control*; D003955:Diagnostic Tests, Routine / Q000592:standards*; D005260:Female; D006801:Humans; D007223:Infant; D008297:Male; D044342:Malnutrition / Q000175:diagnosis*; D015233:Models, Statistical; D015596:Nutrition Assessment; D015588:Observer Variation; D015203:Reproducibility of Results