Variables and Measurement in Research
Types of IVs or Manipulations
Presence/Absence (bivalent)
You have a level of IV that involves the treatment and a level that does not (control group)
Type
Each level of IV involves a different type or version of factor being manipulated
Amount
Each level of IV had a different amount of the treatment
Other Research Designs/Variables
Quasi-Experiment
Type of research design where a comparison is made, as in an experiment, but no random assignment of participants to groups occurs
Quasi-Independent Variable/Subject (attribute) variable
Measurable characteristic of participants that cannot be manipulated (gender, height, weight)
Between subjects
Different participants in each experimental group
Experiences only 1 level of IV
Random assignment into conditions
Within subjects
Same participants in each of the experimental groups
Each participant experiences all levels of IV
Measuring Variables
Qualitative: Nonnumerical participant responses
Quantitative: Numerical data
Measurement: Assigning numbers to indicate the level of a variable
Scaling: Specifies the relationship between the measured variable and the conceptual variable
Nominal/Categorical Scale
Non-ordered category responses, organizing your data into groups
Scores represent a particular characteristic/category, but have no actual value
Gender, hair color, place of birth, political affiliation, diagnostic category, ethnicity
Does not address direction or magnitude of difference between groups/values
Ordinal Scale
Ordered category responses (ranking groups)
Scores indicate whether there is more or less of the variable but not how much
Taste test, order of finish in a race
Ranking addresses the direction of difference (middle value vs highest and lowest) but not the magnitude of difference between values
Interval Scale
Ranked with equal distances between scores corresponding to equal size changes
Temperature scale, IQ scores
Addresses both the direction of difference (rank orderings, like an ordinal scale) and the magnitude of difference between values
The difference between 50/60 degrees is the same as the difference between 60/70 degrees
But no true “0” 0 degrees Fahrenheit isn’t a lack of temperature. Also scores are not ratio of each other
Ratio Scale
Measures differences between groups and the absence of the variable, scores are ratios of each other
Values are anchored by a non-arbitrary zero point: can be measured as having no value
Kelvin scale, reaction time, salary, distance
Called ratio because dividing one point on the scale by another gives a meaningful value
Discrete vs. Continuous Variables
Discrete Variables (nominal/categorical, ordinal date)
Put into groups or groups in ranked order (whole numbers)
Student’s major, enrollment status, gender, ethnicity, etc
Continuous Variables (interval, ratio date)
Each measurement gets a distinct score
GPA, test scores, reaction time
The distinction?
Affects whether a particular statistic can be used