3: Measures Flashcards
operational (or operative) definition
The phenomena to
be measured should be defined in terms of the operations
used to measure them. Essential in experimental research*
- In other words, a behaviour or process (cognitive or physiological) is
defined by the operations that are carried out in order to measure it
A good operational definition is: Reliable and Reproducible
ostensive definitions
The phenomena to be observed
should be carefully described (textually, graphically,
photographically, etc.) and examples can be given.
Common in observational research (it is the basis of
ethograms and systematic observations)
what are some examples of construct validity?(conventional meaning lost)
Bruxism, Alcoholism, PMS, ADHD (sub-types),
aggressiveness/aggression
Scales of measurement when spacing between values is not known
- Nominal scales and ordinal scales
scales of measurement when spacing is known
Interval scales and ratio scales
nominal scales
a scale that labels variables into distinct classifications and doesn’t involve a quantitative value or order
categories, taxonomies, typologies.
* Examples: Male/female;
Liberal/ Conservative/
Democrat; ADD+H/ADD-H;
extroverted / introverted.
* Types of statements: x is
different from y;
assignment of labels
ordinal scales
continuum or spectrum of observations. Ranking within a category is possible; often different names AND certainly different quantities. Absolute values are not known.
* Examples: Low, moderate,
high self-esteem; Ranking
of a race.
* Types of statements: x is
greater than y; assignment
of values
interval scales
has no absolute zero point, i.e., arbitrary.
* In an interval scale, you
have a constant unit and it
satisfies the condition 2-1
= 3-2 = n- (n-1), and here
there is an additive
constant of the form
y=ax+b
(b can be zero or an other
value).
* Common in psychology
and neuroscience: rating
scales, from 0 to 10 (0 does
not mean no liking at all), IQ
scale (0 does not mean no
intelligence).
ratio scales
has an absolute zero point (the absence of the quantity can be indicated). Zero means zero, i.e., nothing.
* In a ratio scale, the linear
transformation of values
must follow the form
y=ax (b is zero, in fact,
must be zero). The Kelvin
scale of temperatures
follows this model. In
other words, with a ratio
scale, all the operations of
arithmetic may be
performed, with the
numerical values
representing absolute
values of the terms.
* Common in psychology
and neuroscience: from
no response to n degree
of response. Example:
score on a memory test.
implications of scales of measurement
- Nominal and ordinal data can be analysed with a number of non-parametric statistical analyses.
- Interval and ratio scales: Analyzed (typically) with parametric statistical analyses.
- Interval scale: spacing between values is known, BUT:
- a score of 120 is not twice
as more as a score of 60
(e.g., two IQ scores).
- a score of 120 is not twice
- Ratio scale: one value is twice as much as another or no quantity of that variable can exist, i.e.:
- a score of 120 is twice as
more as a score of 60 (e.g.,
two scores on a memory
test with 200 items).
- a score of 120 is twice as
- The four scales represent a hierarchy of information yielded (mnemonic: anagram “NOIR”), from little, to substantial.
- Nominal: Purely qualitative information.
- Ordinal: Qualitative with some crude degree of “quantity” (items can be ranked).
- Interval: Quantitative; we know by “how much” the values differ.
- Ratio: Quantitative; we know how much of the quantity exists.
basic types of variables
- Independent (“X”): Treatment, condition, intervention, factor (e.g., conditions: methods of teaching). Independent variables have “levels” (e.g., 2 levels, low and high doses). Also called “experimental variable”, “manipulated variable”.
- Dependent (“Y”): Outcome, response, result, measure (what you measure). The dependent variable is observed and measured.
- Independent vs. dependent: To identify the variables, ask the question “What is the effect of [IV] on [DV]?”
independent variables- quantitative and qualitative
- Independent variables: manipulated variables (with levels of treatment conditions).
- Quantitative: Treatments differ in frequency, amount (e.g., dose), degree, etc.
- Qualitative: Treatments differ in kind
dependent variables- quantitative and qualitative
- Dependent variables: measurable response.
- Quantitative: Usually the case, e.g., a score or duration.
- Qualitative: Special procedures needed, e.g., form of treatment.
- Subject variables / classification or categorization variables / individual-difference variables / grouping variables: not independent variables per se. E.g., sex, age, ethnic background, linguistic background, etc.
Qualitative variables- unordered and ordered
- Qualitative: Represent an attribute and can be assigned a unique category. Used to categorize information.
- Unordered: Cannot be ranked or ordered; mutually exclusive categories. Example: Dead or alive.
- Ordered: Categories can be placed in rank order. Example: Very young, young, adult, geriatric
quantitative variables- discrete and continuous
- Quantitative: Values determined by “counting” or numerical measurements.
- Discrete: Only whole number values. Examples: Number of offspring, number of cells, number of heart attacks.
- Continuous: Infinite number of whole and fractional values. Example: Body weight (60 kg, 105.9 kg, etc.).
types of independent variables
environmental or situational variables
instructional variables
subject, participation, or individual differences variables
environmental or situational variables
Variables referring to
the manipulation of the environment, i.e., treatment, tasks, etc
