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Questionnaire Development Measuring Validity & Reliability James A. Pershing, Ph.D. Indiana University.

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Presentation on theme: "Questionnaire Development Measuring Validity & Reliability James A. Pershing, Ph.D. Indiana University."— Presentation transcript:

1 Questionnaire Development Measuring Validity & Reliability James A. Pershing, Ph.D. Indiana University

2 Definition of Validity Instrument measures what it is intended to measure: Appropriate Meaningful Useful Enables a performance analyst or evaluator to draw correct conclusions

3 Types of Validity Face Content Criterion Concurrent Predictive Construct

4 Face Validity It looks OK Looks to measure what it is supposed to measure Look at items for appropriateness Client Sample respondents Least scientific validity measure Looks Good To Me

5 Content-Related Validity Organized review of format and content of instrument Comprehensiveness Adequate number of questions per objective No voids in content By subject matter experts Balance DefinitionSampleContentFormat

6 Criterion-Related Validity Subject Instrument A Instrument B Task Observation Inventory Checklist Johnyes no Mary no no Leeyes no Pat no no Jimyes yes Scottyes yes Jill no yes Usually expressed as a correlation coefficient (0.70 or higher is generally accepted as representing good validity) How one measure stacks-up against another Concurrent = at same time Predictive = now and future Independent sources that measure same phenomena Seeking a high correlation

7 Construct-Related Validity A theory exists explaining how the concept being measured relates to other concepts Look for positive or negative correlation Often over time and in multiple settings Usually expressed as a correlation coefficient ( 0.70 or higher is generally accepted as representing good validity) THEORYTHEORY Prediction 1 - Confirmed Prediction 2 - Confirmed Prediction 3 - Confirmed Prediction n - Confirmed

8 Definition of Reliability The degree to which measures obtained with an instrument are consistent measures of what the instrument is intended to measure Sources of error Random error = unpredictable error which is primarily affected by sampling techniques Select more representative samples Select larger samples Measurement error = performance of instrument

9 Types of Reliability Test-Retest Equivalent Forms Internal Consistency Split-Half Approach Kuder-Richardson Approach Cronbach Alpha Approach

10 Test-Retest Reliability Administer the same instrument twice to the same exact group after a time interval has elapsed. Calculate a reliability coefficient (r) to indicate the relationship between the two sets of scores. r of+.51 to +.75 moderate to good r over +.75 = very good to excellent T I M E

11 Equivalent Forms Reliability Also called alternate or parallel forms Instruments administered to same group at same time Vary: Calculate a reliability coefficient (r) to indicate the relationship between the two sets of scores. r of+.51 to +.75 moderate to good r over +.75 = very good to excellent Response Set: -- Order -- Wording Stem: -- Order -- Wording

12 Internal Consistency Reliability Split-Half Break instrument or sub- parts in ½ -- like two instruments Correlate scores on the two halves Best to consult statistics book and consultant and use computer software to do the calculations for these tests Kuder-Richardson (KR) Treats instrument as whole Compares variance of total scores and sum of item variances Cronbach Alpha Like KR approach Data scaled or ranked

13 Reliability and Validity So unreliable as to be invalid Fair reliability and fair validity Fair reliability but invalid Good reliability but invalid Good reliability and good validity The bulls-eye in each target represents the information that is desired. Each dot represents a separate score obtained with the instrument. A dot in the bulls-eye indicates that the information obtained (the score) is the information the analyst or evaluator desires.

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