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Nutrient Adequacy Assessment Using Food Consumption Surveys (1986) / Chapter Skim
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Appendix C: Method for Estimating Confidence Intervals
Pages 120-126

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From page 120...
... DESCRIPTION OF METHOD The random variable X describes required intake with a distribution function: G(x)
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From page 121...
... Because daily intakes for any given person vary from day to day, this implies that the same person might on some days be above and on other days be below his or her required intake simply because of day-to-day variability. Presumably then, usual intake, an idealized average intake of persons over a long period, is of interest.
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From page 122...
... . That is, the 95% confidence interval is approximately given by: (W A)
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From page 123...
... . The Nonparametric Approach To implement the probability approach, we must have an estimate of the distribution of actual intake in a specified population, F*
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From page 124...
... were normal) ; however, we believe it will serve as a reasonable approximation for skewed distributions as well.
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From page 125...
... The confidence interval can now be obtained by picking the appropriate percentiles from this distribution. Assumptions of the 95% Confidence Interval The methods of computing 95% confidence intervals assume that the measurements taken from each person are independent of each other and that there are no systematic biases.
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From page 126...
... 1982. Understanding Robust and Exploratory Data Analysis.
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Key Terms

  • confidence interval
  • required intake
  • confidence intervals
  • inadequate intake
  • actual intake

  • appropriate percentiles
  • understanding robust
  • nonparametric method
  • describes required
  • empirical cdf

  • conditional probability
  • x describes
  • distributional properties
  • systematic biases
  • exploratory data

  • implicit assumption
  • random variable
  • random sets
  • bootstrap distribution
  • intervals assume

  • parametric approach
  • variable x
  • original data
  • foods eaten
  • reasonable approximation

  • data set
  • random indices
  • nonparametric estimate
  • data analysis
  • equal probability


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