1. 1 Lecture 2: Types of measurement Purposes of measurement Types and sources of data Reliability and validity Levels of measurement Types of scale

2. 2 Introduction Overview of measurement section of course –lecture 2: introduction –lectures 3-4: screening and diagnostic tests –lectures 5-6: scales Traditions of measurement: –“Clinimetric”: clinical, epidemiological (focus on screening and diagnostic tests) –“Psychometric”: psychology (focus on scales)

3. 3 Introduction (cont) Readings: –Streiner & Norman –Gordis –other

4. 4 Purposes of measurement Clinical –screening, diagnosis, monitoring in individuals Surveillance –planning and monitoring public health and health care in populations Research –measurement of study variables (determinants, outcomes, confounders/modifiers)

5. 5 Sources of data Primary vs secondary Clinical observations Questionnaires and interviews Reportable diseases and registries Health records Administrative databases (hospital discharges, claims, medication prescription) Vital statistics

6. 6 Requirements by purpose of measurement Clinical –discrimination between health and disease relevant to management Surveillance –valid measurement of trends Research –maximize validity of study results

7. 7 Selection of measures Appropriateness to purpose Feasibility Acceptability Cost Validity Reliability

8. 8 Validity of measurements Synonym: accuracy Does it measure what it is intended to? Many types: –face, content “eyeball” test investigator, expert judgment –criterion (lecture 3) –construct (lecture 6)

9. 9 Reliability of measurements Synonyms: reproducibility, precision, consistency Sources of variability? Random error vs systematic error (bias)

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11. 11 Types of reliability: rater Between- and within-rater/observer (inter- and intra-rater observer variation) –At single point in time –Independent ratings –May be random or systematic –Examples: –blood pressure –pathology slides

12. 12 Reliability: stability over time Stability over time/ test-retest (T1 and T2 –Same conditions and rater at T1 and T2. Why? –Random or systematic –Example of systematic error: Regression toward the mean: when subjects initially have extreme values (more likely to be in error than typical values) E.g., population blood pressure screening Questions about undesirable beahviour Uncalibrated instruments

13. 13 Example Measurement of patient depression using clinical rating scale –Sources of variability? –Measurement of inter-rater reliability? –Results for 10 patients: Rater 1: 3 patients are depressed Rater 2: 5 patients are depressed –Conclusion?

14. 14 Types of variables (level of measurement) Continuous (syn. dimensional, quantitative) –interval –ratio Categorical (discrete) –dichotomous, binary –polychotomous nominal ordinal

15. 15 Response scales Categorical or continuous? –Continuous variables can be categorized –Categorical (ordinal) variables can be analyzed as continuous (pseudocontinuous) Example of scales –Visual analogue scale –Likert scale (agree/disgree) –Semantic differential scale

16. 16 Examples of measures to be used in a study: for discussion Sources of data? Level of measurement? Type of response scale? –Use of health services during past year (doctor visits, hospitalization) –Satisfaction with medical care –Use of alcohol and drugs (current and lifetime)