Measures, Reliability, Validity

Scales of Measurement

  • Data are defined through a process known as scaling, which outlines the level of information represented by numeric codes used for data recording.

  • It is crucial to know the type of data before starting research.

  • All research data falls into one of four measurement scales: Nominal, Ordinal, Interval, and Ratio.

Nominal Data

  • Represents categories or labels that have no quantitative properties (i.e., no inherent value).

  • Involves grouping objects into classes, ensuring all members share equivalent attributes.

  • Allows for the fewest statistical tests due to its categorical nature.

Ordinal Data

  • Assigns numbers to indicate rank order among items, suggesting a qualitative distinction.

  • Items can be ranked from high to low, revealing differing amounts of a characteristic without defining the magnitude of differences.

  • No specific value is attributed to intervals between numbers in the scale; the focus is solely on ranking.

Interval Data

  • Uses numbers to define actual scores that describe the magnitude and differences among items.

  • Maintains order and equal magnitude of differences between consecutive scale items.

  • Features equal intervals, but lacks an absolute zero; zero does not signify the total absence of the measured property.

  • Can include negative values.

Ratio Data

  • The most precise scale of measurement with scores related through a single dimension.

  • Separated by equal intervals, it includes an absolute zero indicating the total absence of the variable measured.

Measurement Scale Identification Exercises

  • Fever (body temperature): Interval

  • Telephone number: Nominal

  • Number of rolls of toilet paper: Ratio

  • Length of a class (in minutes): Ratio

  • Anxiety score (measured on a scale): Interval

  • Religious persuasion: Nominal

  • Distance a student commutes: Ratio

  • Top ten best dressed people: Ordinal

  • Rank on a self-esteem scale: Ordinal

  • Number of dates last month: Ratio

Reliability

  • Refers to the consistency of a measurement over time.

Components of Reliability

  1. True Score: The actual value of a variable, representing the “real” score.

  2. Measurement Error: Variability in scores indicating how much the measurement deviates from the true score.

Types of Reliability

  1. Test-Retest Reliability: Measurement taken multiple times to check consistency.

  2. Internal Consistency: Responses measured at one point in time.

    • Split-Half Reliability: Correlates total scores on one half of the measure against the other half.

    • Cronbach’s Alpha: Correlates each item with every other item on the measure to assess consistency.

  3. Inter-Rater Reliability: Agreement among different observers regarding events.

Validity

  • Indicates the capacity of a measurement to accurately reflect the variable in study.

  • This assesses how well an operational definition aligns with the theoretical meaning of the variable.

Types of Validity

  1. Construct Validity: Measures the adequacy of the operational definition to represent the variables.

    • Face Validity: Assessment based on surface appearances.

    • Predictive Validity: Ability to forecast future behavior.

    • Concurrent Validity: Comparison of test results with behavior.

Reactivity

  • Refers to how the awareness of being measured can alter an individual’s behavior.