Level Of Measurement

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Instructional Measurement

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Level Of Measurement

  1. 1. Research Methods I Kinds of Data and Levels of Measurement
  2. 2. Review <ul><li>The Scientific Method – Conducting a Study </li></ul><ul><ul><li>Understanding Nature of Problem </li></ul></ul><ul><ul><ul><li>Literature Review </li></ul></ul></ul><ul><ul><ul><li>Research Question - Hypothesis </li></ul></ul></ul><ul><ul><li>Test Hypothesis empirically </li></ul></ul><ul><ul><ul><li>Deciding on measurements </li></ul></ul></ul><ul><ul><ul><li>Data collection </li></ul></ul></ul><ul><ul><ul><li>Data analysis </li></ul></ul></ul><ul><ul><li>Interpret results and draw conclusions </li></ul></ul>
  3. 3. Variables and Measurements <ul><li>Variables: </li></ul><ul><li>Characteristics that can take on different values for different members of a group </li></ul><ul><ul><li>Independent variables </li></ul></ul><ul><ul><li>Dependent variables </li></ul></ul><ul><li>Construct: </li></ul><ul><li>Hypothetical concepts that describe and explain behavior (e.g. self-esteem) </li></ul><ul><ul><li>operational definition of construct </li></ul></ul><ul><li>Measurements: </li></ul><ul><li>“ Assignment of numbers to aspects of objects, persons or events.” </li></ul>
  4. 4. Kinds of Data Levels of Measurement <ul><li>Qualitative / Discrete Data </li></ul><ul><ul><li>Separate, indivisible categories (e.g. male, female) </li></ul></ul><ul><ul><ul><li>Nominal (categorical) </li></ul></ul></ul><ul><ul><ul><li>(Ordinal) </li></ul></ul></ul><ul><li>Quantitative / Continuous Data </li></ul><ul><ul><li>Infinite number of possible values that fall between two observed values </li></ul></ul><ul><ul><ul><li>Interval </li></ul></ul></ul><ul><ul><ul><li>Ratio </li></ul></ul></ul>
  5. 5. Nominal Level of Measurement <ul><li>Data in a set of categories that have different names </li></ul><ul><ul><li>It is arbitrary; no logical ordering </li></ul></ul><ul><ul><li>Has to do with names </li></ul></ul><ul><ul><ul><li>E.g. gender, race, religion, kind of profession </li></ul></ul></ul><ul><li>N-category nominal scales </li></ul><ul><ul><ul><li>Dichotomies (gender) </li></ul></ul></ul><ul><ul><ul><li>Five category (ethnicity: African-American, Caucasian, Asian, Native American, Hispanic) </li></ul></ul></ul>
  6. 6. Ordinal Level of Measurement <ul><li>Ranked in terms of magnitude </li></ul><ul><li>Distances between variables or exact amount of variables does not have to be known </li></ul><ul><li>In papers grouped ordinal data is often used (how many people are in each category </li></ul>
  7. 7. Ordinal Level of Measurement – Likert Scales <ul><li>Item pool concerning referent in question </li></ul><ul><li>Level of agreement to each statement </li></ul><ul><li>Average responses to get final score </li></ul><ul><li>Logical sequence (order) </li></ul><ul><li>May be treated as continuous variables in analyses even though they are actually ordinal </li></ul>
  8. 8. Interval Level of Measurement <ul><li>Ordered categories that are all intervals of exactly the same size </li></ul><ul><li>For interval data zero is an arbitrary point </li></ul><ul><ul><li>Does not mean the absence of measured characteristic </li></ul></ul><ul><li>Arithmetic operations can be performed with interval data </li></ul><ul><ul><li>There are some limitations </li></ul></ul>
  9. 9. Ratio Level of Measurement <ul><li>Ratio data is like interval data, except the origin of the scale represents the absence of the characteristic measured </li></ul><ul><li>Examples of ratio level measurements are </li></ul>
  10. 10. Is our measure valid? <ul><li>Definition: </li></ul><ul><li>Validity describes how well as measure actually assesses what you want it to </li></ul><ul><li>Decide how to measure variables </li></ul><ul><li>Describes soundness and appropriateness of a measure for purpose of study </li></ul>
  11. 11. Validity <ul><li>Content validity : Does measure cover all different domains of the concept? </li></ul><ul><ul><li>Face validity : How is measure viewed by others as covering the concept? </li></ul></ul><ul><ul><li>Sampling-content validity: everything covered? </li></ul></ul><ul><li>Criterion validity : How well do measures of convenience assess criterion of interest </li></ul><ul><li>Construct validity : Does the measure assess underlying theoretical construct? </li></ul>
  12. 12. Reliability <ul><li>To which extent do two sets of measurements of the same characteristic on the same people duplicate each other </li></ul><ul><li>A reliable measure is free of measurement error </li></ul><ul><ul><li>Test-retest reliability (same people, different time) </li></ul></ul><ul><ul><li>Inter-rater agreement (same people, same time) </li></ul></ul><ul><ul><li>Internal-consistency (consistency of answers across items) </li></ul></ul><ul><ul><li>Problem with measurement error and reliability - variability </li></ul></ul>

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