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Modeling preferences to calibrate vulnerability scoring…

What is Conjoint analysis?

Conjoint analysis can speed up expert consultations by offering an objective mean to compile expert opinions.

  • Conjoint analysis originated in mathematical psychology by psychometricians.

  • often used to evaluate how people make decisions between a set of different options when considering a number of criteria at the same time (conjoint features; “trade-offs”).

Measurement framework

The Joint Intersectoral Analysis Framework (JIAF) is a theoretical generic measurement framework to be used for Humanitarian needs assessment. It specifies three distinct and complementary components of humanitarian severity and vulnerability indexes:

  • Basic Needs & Living standards
  • Coping Capacity
  • Well Being & Community integration

This generic model can be contextualised: different sub-indicators might be used for each of the 3 components depending on cultural and political situations.

Define the combined alternatives to be compared

  • participants rate their preferences for profiles with different combinations of the attributes or criteria.

  • CA then allows to “decompose” or reverse-engineer these ratings into estimates of how important each criteria or attribute is to a participant’s ranking decisions

Utility scales & Agreement levels

Estimating the contribution of each potential answers

  • Utility values indicate the overall contribution of each attribute to how the profiles were rated (e.g. whether number of meals is more important in vulnerability scoring than access to safe water).

  • A higher “utility” estimate indicates that this level contributes to a higher vulnerability than the level with the lower utility estimate (it does not give an absolute value for the utility of an option, but rather assumes a reference alternative).

  • Standard deviation for each level within model allows to better understand how homogenous the group of experts is with respect to one level.

Importance of each criteria

  • Importance of each criteria represent the average importance as estimed from all experts.

  • Importance values will then be used as the weights for each attribute inside each of our three dimensions.

  • Importance values sum to 100%.

Expert Review