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Improving Information for Social Policy Decisions -- The Uses of Microsimulation Modeling Volume II, Technical Papers (1991) / Chapter Skim
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Pages 286-290

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From page 286...
... COHEN ET AL. Analysis of Variance Methods for Sensitivity Analysis and External Validation The variability observed for these projections has a distinct structure, which can be analyzed by using analysis of variance, since the 16 observations for every response obey a 4 x 2 x 2 factorial design with one replication per cell.
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From page 287...
... 287 of C)
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From page 288...
... If this analysis when repeated gave similar results in comparable situations, it would be reasonable to direct attention to research on aging modules, with adjustment second, and algorithms for allocating income on a monthly basis third. The only significant interaction
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From page 289...
... Therefore, the mean square error cannot be used to create confidence intervals for measuring agreement between estimates and comparison values. However, the size of the main effects, interactions, and error can be compared to the distances between model estimates and the comparison values to examine such questions as whether all important components were included in the sensitivity analysis; whether interactions were ignorable, with the result that the component alternatives can
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From page 290...
... Finally, even if we had been able to compute confidence intervals to identify model estimates that were not significantly different from comparison values, it was also of value to identify alternative modules that resulted in model estimates that, while significantly different, were closer to the comparison values than the grand mean. In other words, there is value in knowing which alternatives "are headed in the right direction." This is the objective of the last column of Table 4.
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Key Terms

  • sensitivity analysis
  • comparison values
  • model versions
  • confidence intervals
  • variability due

  • external validation
  • input data
  • confidence interval
  • aging module
  • current months

  • monthly basis
  • model validation
  • variance due
  • sampling variability
  • square error


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