1. MEASUREMENT: RELIABILITY AND VALIDITY
Reliability: dependability or consistency
The numerical results produced by by an indicator do not vary because of characteristics of the measurement process or measurement instrument itself.
3 types of reliability:
Stability reliability
Representative reliability
Equivalence reliability

2. Stability reliability
Rel. across time. Does the measure deliver the same answer when applied in different time periods?
Weight-scale example
Test-retest (reliability
Representative reliability
Rel across subpopulations or groups.
Does the indicator deliver the same result when applied to different groups?
Ex: measure of critical thinking---for gender/religion...

3. Equivalence reliability:
Applies when researchers use multiple measures (several items in a questionnaire measuring the same construct)
Does the measure yield consistent result across different indicators?
Ex: nationalism –10 items
İntercoder reliability
When observers or raters agree with each other
Ex: content analysis studies

4. VALIDITY
How well the conceptual and operational definitions mesh with each other
The better the fit, the greater the validity
More difficult to achieve than reliability
Cannot have absolute confidence in validity
Same as epistemic relation
Hypothetical correlation between the indicator and the construct

5. Four types of validity:
Face validity
Content validity
Criterion validity
Concurrent validity
Predictive validity
Construct validity
Divergent
discriminant

6. Face val: judgement of the researcher
Content val: is the full content of the definition represented in a measure?
Ex: definition of feminism—equality in arts, politics, family, work, authority relations....
Criterion : uses some standard or criterion to indicate a construct accurately
The validity of an indicator is verified by comparing it with another measure of the same construct
2 types
1. concurrent: an indicator must be associated with a preexisting indicator that is judged to be valid.
Ex: two diiferent measures of totalitarianism should be highly correlated

7. 2. predictive validity:
An indicators predicts a future event that is logically related to a construct
İt cannot be used for all measures
Should not be confused with prediction in hypothesis testing
Ex: GRE test (or LES) has high predictive validity if the graduate students who took higher grades in GRE or LES do well in graduate program.
Ex: measure of political conservatism—should give higher scores with AKP members, but lower scores with DTP members.

8. Construct validity
İf the measure is valid do the various indicators operate in a consistent manner?
For measures with multiple indicators
Convergent validity
Applies when multiple indicators converge or associate with one another
Whether multiple measures of the same construct hang together or operate in a similar manner
Discriminant validity
Opposite of convergent
Means that the indicators of one construct hang together , but also diverge or negatively associated with opposing constructs
Ex: conservatism—liberalism

9. Relationship between reliability and validity
Reliability is necessary for validity
But it does not guarantee that a measure will be valid
Not a suficient condition for validity
A measure may produce the same result over and over again, but it does not mean that it fits the construct
Sometimes as validity increases reliability is more diificult to attain. This occurs when a construct is highly abstract (alienation ex)

11. Other uses of the terms reliability and validity
Internal validity:
There are no errors internal to the design of the research
External validity:
İs used primarily in experimental research
It is the ability to generalize findings from one setting to a broad range of settings
Statistical validity:
Means that the correct statistical procedure is chosen and its assumptions are fully met.
Ex: race 1.white 2. african-american 3. asian
İt does not make any sense to say that the average race is 1,5.

12. Levels of Measurement Continous and discrete variables:
Continous variables have an infinite number of values or attributes that flow along a continuum.
Ex: temparature, age, income, amount of schooling,...
Discrete variables:
Have relatively fixed set of seperate values or variable attributes
İnstead of a continuum, they contain distinct categories
Ex: gender (male/female); religion (muslim/protestant/catholic...)
Whether a variable continous or discrete affects its measurement level

13. Nominal: indicates only that there is a difference among categories
Nominal measures
Ordinal measures
İnterval measures
Ratio measures
Nominal: indicates only that there is a difference among categories
Ex: religion, marital status, gender
Ordinal: indicates a difference and categories can be ordered or ranked
Ex: letter grades (A B C), strongly agree-strongly disagree
İnterval: it can specifiy the amount of distance between categories
Ex: (IQ scores, scores on several scales)
Has arbitrary zero
Ratio: there is a true zero which makes it possible to state relations in terms of proportion or ratios
Ex: income, years of schooling,

14. Nominal—discrete
Ordinal—discrete
Continous variables can be measured at the interval or ratio level
A ratio level measurement can be turned into an internal, ordinal, or nominal.
The interval level can always be turned into an ordinal or nominal, but not the other way around.
The ratio level is rarely used in social sciences