Modeling and Multivariate Methods - SAS

Chapter 17 Correlations and Multivariate Techniques 453
Examples
In addition to saving the distance values for each row, a column property is created that holds one of the
following:
• the distance value for Mahalanobis Distance and Jackknife distance
• a list containing the UCL of the T 2 statistic
Item Reliability
Item reliability indicates how consistently a set of instruments measures an overall response. Cronbach’s α
(Cronbach 1951) is one measure of reliability. Two primary applications for Cronbach’s α are industrial
instrument reliability and questionnaire analysis.
Cronbach’s α is based on the average correlation of items in a measurement scale. It is equivalent to
computing the average of all split-half correlations in the data table. The Standardized α can be requested if
the items have variances that vary widely.
Note: Cronbach’s α is not related to a significance level α. Also, item reliability is unrelated to survival time
reliability analysis.
To look at the influence of an individual item, JMP excludes it from the computations and shows the effect
of the Cronbach’s α value. If α increases when you exclude a variable (item), that variable is not highly
correlated with the other variables. If the α decreases, you can conclude that the variable is correlated with
the other items in the scale. Nunnally (1979) suggests a Cronbach’s α of 0.7 as a rule-of-thumb acceptable
level of agreement.
See “Computations and Statistical Details” on page 454 for computations for Cronbach’s α.
Impute Missing Data
To impute missing data, select Impute Missing Data from the red triangle menu for Multivariate. A new
data table is created that duplicates your data table and replaces all missing values with estimated values.
Imputed values are expectations conditional on the nonmissing values for each row. The mean and
covariance matrix, which is estimated by the method chosen in the launch window, is used for the
imputation calculation. All multivariate tests and options are then available for the imputed data set.
This option is available only if your data table contains missing values.
Examples
Example of Item Reliability
This example uses the Danger.jmp data in the Sample Data folder. This table lists 30 items having some
level of inherent danger. Three groups of people (students, nonstudents, and experts) ranked the items
according to perceived level of danger. Note that Nuclear power is rated as very dangerous (1) by both
students and nonstudents, but is ranked low (20) by experts. On the other hand, motorcycles are ranked
either fifth or sixth by all three judging groups.