Decision Sciences Journal
Volume 31, Number 3
Summer 2000
Sensitivity Analysis for Dependent Variables
Terence Reilly
Mathematics Dept., Babson College, Babson Park, MA 02157, email:
reilly@babson.edu
Abstract. Decision analysts use sensitivity analysis
to identify influential variables, to determine which input variables
to model stochastically, and to characterize scenarios that could
affect a change in the rank ordering of the alternatives. A frequently
recommended sensitivity analysis technique is “one-way”
sensitivity analysis, which determines a variable’s influence
by the degree to which the objective function changes as that
variable is varied while all other variables are held fixed.
Disadvantages of one-way analysis are that it measures the influence
of only one variable at a time and it assumes independence among
the input variables. Clearly, however, there are situations when
dependencies exist among the input variables that could possibly
affect the sensitivity analysis results. This research develops
a strategy that incorporates dependence relations among the input
variables into the sensitivity analysis using rank correlations.
Only decision problems with a finite number of alternatives and
continuous state variables are considered.
Subject Areas: Correlations, Decision Theory, Dependence
Measures, and Sensitivity Analysis. |