Weighted Application Blank WAB Process

1
Weighted Application Blank (WAB) Process

• Chose criterion
• Identify criterion groups (e.g., low and high
  absenteeism)
• 3) Select items (the more the better)
• 4) Determine response categories (e.g., true,
  false continuum)
• 5) Determine the weights for each item (e.g., use
  of regression)
• 6) Estimate amount of shrinkage (e.g.,
  cross-validation)
• 7) Evaluate hold-out group scores
• 8) Determine cut-off scores

2
Some WAB Concerns

• No single WAB is useful for all jobs
• Comparability of sample (generalization)
• Change in criterion
• Change in nature of job(s) across time
• Legal issues (e.g., use of demographic data)
• 6) Changes in the organization

3
Biographical Data (Bio-Data) Process

• Choose a specific job
• Use of job analysis to select items (use of FJA
  to cover broader job domains e.g.,
  responsibility, work conditions) and define life
  history domain (e.g., criterion to use)
• Form hypotheses regarding life history
  background and experience
• Construct bio-data items (cover relevant
  experience domains)
• Screen and pilot-test the items
• Score bio-data items (single versus multiple
  scores)

4
Sample Biographical Information Blank Items

• During high school, how many times did you make
  the honor roll?
• How much freedom or independence did your
  parents allow you in grade school?
• How important did your favorite high school
  teachers stress discipline in the
• classroom?
• How many times did you change schools before you
  were sixteen years old?
• Compared to other people in high school, how
  many friends did you have?
• How old were you when you spent your first week
  (or more) away from your
• parents?
• How bothered are you if you a job is left
  undone?
• How often do you read craft and mechanics
  magazines?
• How quickly do you normally work?
• How well do you feel you can understand the
  feelings of others?
• How well do you tolerate performing routine
  tasks?

5
Bio-Data Why does it work?

• Use of life history items e.g., personal
  background, life experiences, interests (past
  behavior is best predictor of future behavior)
• Only relevant (empirically significant) items
  are selected
• Correlation between BIB content and criterion
• Wide range of information (lots of different
  questions and types)

6
Bio-Data (cont)

• Reliability .60 to .80 across several studies
  higher for more verifiable items
• Validity Many validity coefficients above .30
• Accuracy Some distortions exist. Mainly on
  unverifiable items (e.g., interests, preferences)
  and more if desirability of answers is apparent
  (e.g., faking can occur)

7
Some Bio-Data Issues

• Situational specificity
• Need large sample to construct properly
• Assumption of a correct life history
• Pure empirical approach (e.g., versus content
  approach)
• Legal issues (e.g. adverse impact, validity,
  reliability)