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Measurement and Data Quality

Measurement and Data Quality. Measurement. The assignment of numbers to represent the amount of an attribute present in an object or person, using specific rules Advantages: Removes guesswork Provides precise information Less vague than words. Levels of Measurement.

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Measurement and Data Quality

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  1. Measurement and Data Quality

  2. Measurement • The assignment of numbers to represent the amount of an attribute present in an object or person, using specific rules • Advantages: • Removes guesswork • Provides precise information • Less vague than words

  3. Levels of Measurement • There are four levels (classes) of measurement: • Nominal(assigning numbers to classify characteristics into categories) Gender, religion • Ordinal(ranking objects based on their relative standing on an attribute) "very dissatisfied," "somewhat dissatisfied," "somewhat satisfied," or "very satisfied." • Interval (objects ordered on a scale that has equal distances between points on the scale) Fahrenheit scale of temperature • Ratio (equal distances between score units; there is a rational, meaningful zero) amount of money you have in your pocket right now • A variable’s level of measurement determines what mathematic operations can be performed in a statistical analysis.

  4. Errors of Measurement • Obtained Score = True score ± Error • Obtained score:An actual data value for a participant (e.g., anxiety scale score) • True score:The score that would be obtained with an infallible measure • Error:The error of measurement, caused by factors that distort measurement

  5. Factors That Contribute to Errors of Measurement • Situational contaminants • Transitory personal factors (e.g., fatigue) • Response-set biases • Administration variations • Item sampling

  6. Question Is the following statement True or False? • The true score is data obtained from the actual research study.

  7. Answer • False • The true score is the score that would be obtained with an infallible measure. The obtained score is an actual value (datum) for a participant.

  8. Psychometric Assessments • A psychometric assessmentis an evaluation of the quality of a measuring instrument. • Key criteria in a psychometric assessment: • Reliability • Validity

  9. Reliability • The consistency and accuracy with which an instrument measures the target attribute • Reliability assessments involve computing a reliability coefficient. • Reliability coefficients can range from .00 to 1.00. • Coefficients below .70 are considered unsatisfactory. • Coefficients of .80 or higher are desirable.

  10. Three Aspects of Reliability Can Be Evaluated • Stability • Internal consistency • Equivalence

  11. Stability • The extent to which scores are similar on two separate administrations of an instrument • Evaluated by test–retest reliability • Requires participants to complete the same instrument on two occasions • Appropriate for relatively enduring attributes (e.g., creativity)

  12. Internal Consistency • The extent to which all the items on an instrument are measuring the same unitary attribute • Evaluated by administering instrument on one occasion • Appropriate for most multi-item instruments • The most widely used approach to assessing reliability • Assessed by computing coefficient alpha (Cronbach’s alpha) • Alphas ≥.80 are highly desirable.

  13. Question When determining the reliability of a measurement tool, which value would indicate that the tool is most reliable? • 0.50 • 0.70 • 0.90 • 1.10

  14. Answer c. 0.90 • Reliability coefficients can range from 0.0 to 1.00. Coefficients of 0.80 or higher are desirable. Thus, a coefficient of 0.90 would indicate that the tool is very reliable. A value greater than 1.00 for a coefficient would be an error.

  15. Equivalence • The degree of similarity between alternative forms of an instrument or between multiple raters/observers using an instrument • Most relevant for structured observations • Assessed by comparing agreement between observations or ratings of two or more observers (interobserver/interrater reliability)

  16. Reliability Principles • Low reliability can undermine adequate testing of hypotheses. • Reliability estimates vary depending on procedure used to obtain them. • Reliability is lower in homogeneous than heterogeneous samples. • Reliability is lower in shorter than longer multi-item scales.

  17. Validity • The degree to which an instrument measures what it is supposed to measure • Four aspects of validity: • Face validity • Content validity • Criterion-related validity • Construct validity

  18. Face Validity • Refers to whether the instrument looks as though it is an appropriate measure of the construct • Based on judgment; no objective criteria for assessment

  19. Content Validity • The degree to which an instrument has an adequate sample of items for the construct being measured • Evaluated by expert evaluation, often via a quantitative measure—the content validity index (CVI)

  20. Question Is the following statement True or False? • Face validity of an instrument is based on judgment.

  21. Answer • True • Face validity refers to whether the instrument looks like it is an appropriate measure of the construct. There are no objective criteria for assessment; it is based on judgment.

  22. Criterion-Related Validity • The degree to which the instrument is related to an external criterion • Validity coefficient is calculated by analyzing the relationship between scores on the instrument and the criterion. • Two types: • Predictive validity: the instrument’s ability to distinguish people whose performance differs on a future criterion • Concurrent validity: the instrument’s ability to distinguish individuals who differ on a present criterion

  23. Construct Validity • Concerned with these questions: • What is this instrument really measuring? • Does it adequately measure the construct of interest?

  24. Some Methods of Assessing Construct Validity • Known-groups technique • Testing relationships based on theoretical predictions • Factor analysis

  25. Criteria for Assessing Screening/Diagnostic Instruments • Sensitivity: the instruments’ ability to correctly identify a “case”—i.e., to diagnose a condition • Specificity: the instrument’s ability to correctly identify noncases, that is, to screen out those without the condition • Likelihood ratio: Summarizes the relationship between sensitivity and specificity in a single number • LR+: the ratio of true positives to false positives • LR-: the ratio of false negatives to true negatives

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