HUMAN RESOURCES SELECTION
綜合能力考核表詳細內容
HUMAN RESOURCES SELECTION
HUMAN RESOURCES SELECTION
SELECTION
Selection involves:
assessment or measurement of job relevant individual differences,
using these measures to infer how individuals are likely to behave on the job
Making hire/no hire decisions based on these inferences
What Do We Measure?
Our predictors:
Knowledge
Skills
Abilities
Cognitive
Physical
Personality
Vocational Interests
Life history
Behavior on the Job
Typical criteria :
Job performance
Job satisfaction
Turnover
Organization Commitment
Selection Process
Measurement
Ensuring that selection devices are reliable and valid
Decision Making
Combining information about a person to make a hiring decision
Evaluation
Making sure that hiring decisions increase the efficiency and profitability of the organization
Important Statistical Methods
Correlation Analysis – is used to determine the degree of relationship between two variables
Pearson Product Moment correlation coefficient (r) is a numerical index that indicates the direction and degree of linear relationship between two variables
The Correlation Coefficient “r”
The numerical value of “r” ranges from –1.0 to +1.0
The sign of the correlation indicates the direction of the relationship
The magnitude of “r” indicates the strength of the relationship
The numerical index is appropriate only for describing linear relationships
Regression Analysis
Regression analysis is used to model a linear relationship between a dependent variable and one or more independent variables (or predictors )
Equation : Y = a+ bX
Important concepts in Selection
Reliability-- the extent to which a selection test provides consistent results
Validity – the extent to which a test measures what it purports to measure
Measuring Reliability
Test-Retest – examines the consistency of a test over time
Inter-rater – examines consistency across raters
Internal consistency- examines the extent to which all items on a test measure the same construct
Measures of Validity
Validity deals with issues of :
whether the test is an adequate measure of the characteristic it supposedly measures
Whether inferences and actions based on test scores are appropriate
Validity
Content validity – whether or not a test is representative of a constructs domain
Construct validity – whether or not a test measures the traits or abilities it is proposed to measure
Criterion Validity
Whether or not scores on a test are related to an important job related criterion
Predictive – administering a selection test and collecting criterion information later from the same applicants
Concurrent – Administering a selection test to current incumbents and obtaining criterion information at essentially the same time
Concerns in criterion validation
Range Restriction
Sample
Size
How Representative
Dynamic criterion
Validity generalization through the use of meta-analysis
Decision Making
Additive models- test scores are are converted to a common metric sometimes weighted then summed the person with the highest score is hired
Multiple cutoffs – A non- compensatory model in which applicants are required to have minimum scores on each test
Multiple Hurdle – sequential decision making in which applicants pass through several selection stages with some individuals being rejected at each stage
Profile Matching – assumes that there is an ideal level of predictor variables that an applicant should have rather than a minimum that must be met or exceeded.
Selection systems and minority groups
Differential validity
Differential prediction
Adverse Impact
Adjusting test scores of minority group members
Bonus points
Within-group norming
Separate cutoffs
Top down selection from separate lists
Banding
HUMAN RESOURCES SELECTION
HUMAN RESOURCES SELECTION
SELECTION
Selection involves:
assessment or measurement of job relevant individual differences,
using these measures to infer how individuals are likely to behave on the job
Making hire/no hire decisions based on these inferences
What Do We Measure?
Our predictors:
Knowledge
Skills
Abilities
Cognitive
Physical
Personality
Vocational Interests
Life history
Behavior on the Job
Typical criteria :
Job performance
Job satisfaction
Turnover
Organization Commitment
Selection Process
Measurement
Ensuring that selection devices are reliable and valid
Decision Making
Combining information about a person to make a hiring decision
Evaluation
Making sure that hiring decisions increase the efficiency and profitability of the organization
Important Statistical Methods
Correlation Analysis – is used to determine the degree of relationship between two variables
Pearson Product Moment correlation coefficient (r) is a numerical index that indicates the direction and degree of linear relationship between two variables
The Correlation Coefficient “r”
The numerical value of “r” ranges from –1.0 to +1.0
The sign of the correlation indicates the direction of the relationship
The magnitude of “r” indicates the strength of the relationship
The numerical index is appropriate only for describing linear relationships
Regression Analysis
Regression analysis is used to model a linear relationship between a dependent variable and one or more independent variables (or predictors )
Equation : Y = a+ bX
Important concepts in Selection
Reliability-- the extent to which a selection test provides consistent results
Validity – the extent to which a test measures what it purports to measure
Measuring Reliability
Test-Retest – examines the consistency of a test over time
Inter-rater – examines consistency across raters
Internal consistency- examines the extent to which all items on a test measure the same construct
Measures of Validity
Validity deals with issues of :
whether the test is an adequate measure of the characteristic it supposedly measures
Whether inferences and actions based on test scores are appropriate
Validity
Content validity – whether or not a test is representative of a constructs domain
Construct validity – whether or not a test measures the traits or abilities it is proposed to measure
Criterion Validity
Whether or not scores on a test are related to an important job related criterion
Predictive – administering a selection test and collecting criterion information later from the same applicants
Concurrent – Administering a selection test to current incumbents and obtaining criterion information at essentially the same time
Concerns in criterion validation
Range Restriction
Sample
Size
How Representative
Dynamic criterion
Validity generalization through the use of meta-analysis
Decision Making
Additive models- test scores are are converted to a common metric sometimes weighted then summed the person with the highest score is hired
Multiple cutoffs – A non- compensatory model in which applicants are required to have minimum scores on each test
Multiple Hurdle – sequential decision making in which applicants pass through several selection stages with some individuals being rejected at each stage
Profile Matching – assumes that there is an ideal level of predictor variables that an applicant should have rather than a minimum that must be met or exceeded.
Selection systems and minority groups
Differential validity
Differential prediction
Adverse Impact
Adjusting test scores of minority group members
Bonus points
Within-group norming
Separate cutoffs
Top down selection from separate lists
Banding
HUMAN RESOURCES SELECTION
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