For each of the six possible solution strategies
accompanying each of the seven vignettes in the
Everyday Situational Judgment Inventory (Movies),
the sample's mean rating (excluding the rating of the
participant of interest) was subtracted from the
participant's rating. These computations resulted in a
vector of six simple difference scores for each
participant, for each of the seven vignettes, and thus
7 ×N vectors in all. Then, the vectors of difference
scores were each multiplied by the inverse of the
variance–covariance matrix of the six possible response
strategies from which the difference scores
were created. The resulting 6 × 1 vector was then
multiplied by the transpose of the original differencescore
vector, resulting in a scalar, called the
Mahalanobis distance, or D2
. These computations,
then, resulted in seven D2 values per individual, one
per vignette, and thus 7 ×N in all. The D2 values were
then averaged, and their square root was taken to
return the value to its original metric. The individual's
total score for the Everyday Situational Judgment Inventory (Movies) was determined by averaging the
resulting vignette-level values.