WEEK 3- L6.2 rd- measurement

Question 1

purpose of measurement

Answer 1

to link theories to the real world
connecting the two levels- turns abstract concepts to indicator variables

Question 2

concept is..

Answer 2

a construct derived by mutual agreement from mental images that summarizes collections of related experiences/observations.
=> defining democracy
should cover multiple attributions/ indicators

Question 3

constructs and indicators- what does “avoid reification of concepts mean”?

Answer 3

concepts such as democracy are still abstract even if we identify some common attributes

Question 4

conceptual goodness acc. to gerring (8)

Answer 4

**1. familiarity- **established usage
**2. resonance- **does it have a cognitive click
3. parsimony- as simple as possible
**4. coherence- **internal consistency (are the different attributes related with one another)
**5. differentiation- **external diferentation/ boundedness
**6. depth- **ability to bundle many different characteristics/ attributes
7. theoretical utility- is it useful for theory building
**8. field utility- **can it capture new entities, reconceptualization without using meaning- and becoming empty

Question 5

measurement examples (2)

Answer 5

1. simple concepts (undimensional): age
2. complec concepts (multidimensional): corruption, democracy, prejudice

Question 6

what is corruption as a concept?

Answer 6

the misuse of position for private gain

Question 7

what’s the indicators of corruption?

Answer 7

perception fo corruption by business people, experience by public, prosection of public officials

Question 8

what’s the observation of corruption?

Answer 8

expert survey, public survey, court records

Question 9

what are the steps to conceptualize multidimensional concepts?

Answer 9

1. concept
2. indicator
3. observation

Question 10

measures should be.. (2)

Answer 10

1. unbiased: free of systematic errors = accuracy = validity
2. efficient: low variance and random errors = precision = reliability

Question 11

unbiased means…

Answer 11

high validity

Question 12

efficient means…

Answer 12

high reliability

Question 13

being high on reliability means…

Answer 13

the dots are very close to eachother, we always get the same results (we can rely on it) but are the results valid? we don’t know

Question 14

being high on validity means…

Answer 14

although the dots are not close to eachother, they’re close to the actual relaity. we can’t rely on them that they’re similar but we can say that the results are valid.

Question 14

different types of validity and reliability

Answer 14

**1. research design
*** internal validity: causal inferences
* external validity: generalizability

**2. measurement
*** measurement reliabilty: consistency and precision
* measurement validity: accuracy

Question 15

“measurement reliabiltyand validity are necessary requirements for internal and external validity”

Answer 15

correct!

Question 16

measurement error

Answer 16

observed measurement = true score + error score
error score: random error+ systematic error

Question 17

types of measurement error, which is always wrong?

Answer 17

1. random error (decreases reliability)
2. systematic error (always wrong)

Question 18

how can measurement reliability be assesed? (3)

types of measurement reliability

Answer 18

1. test-retest reliability (stabilty over time)
2. internal consistency (accross different indicators)
3. intercoder/rater reliability (consistency accross researchers)

Question 19

how can overall reliabilty be reported?

Answer 19

for internal consistency: reliability coefficient
ranges from .00 to 1.00
.7 is minimum,.8 is good

Question 20

what are examples of mesurement reliability coefficients?

Answer 20

cronbachs alpha and split half method

Question 21

three ways of assesing measurement validity

more difficult bc we dont’ know the real score

Answer 21

1. face validity- judgement based (not reported)
**2. content validity **(theory-based): covering all dimensions? deals with intention
3. criterion/ construct validity:
a. concurrent: criteria is available - there’s an external criteria that’s correlated
b. predictive: criteria will be available in the future (SAT?) - there’s an external criteria that’s correlated
c. convergent: correlating with existing measures
*d. discriminant: *doesn’t overlap with theoretically different stuff does your concept distinguish?

Question 22

what are the types of criterion validity?

Answer 22

1. concurrent- predictive
2. convergent
3. discriminant

Question 23

when the score is always the same, but it’s wrong

Answer 23

reliabilty: yes
validity: none

Question 24

when there’s some random error, but it’s close to the real score

Answer 24

reliability: yes with random error
validity: yes

Question 25

is reliability necessary for validity?

Answer 25

yes reliability is necessary for validity

Question 26

3 types of triangulation

Answer 26

1. data triangulation- using different sources or measures
2. investigator triangulation- different researcher
3. methodological triangulation- using different methods

Question 27

3 possible outcomes of triangulation

Answer 27

1. convergence - same
2. inconsistency- some differences
3. contradiction- opposite

Question 28

why should we use triangulation?

Answer 28

it help to identify problems- learning process- learning inconsistencies allow to develop better measures

Question 29

principles of data quality

Answer 29

1. transperancy
2. replication- new data collection
3. verification- re analysis of existing data

Question 30

(…) is necessary for (…)

Answer 30

reliability is necessary for validity

Question 31

what’s face validity

Answer 31

the indicator intuitively seems like a goo d measure of the concept

Question 32

what’s content validity

Answer 32

the extent to which the indicator covers the full range of the concept, covering each of its different aspects.

Question 33

what’s construct validity

Answer 33

examines how well the measure confirms to our theoretical expectations

looks at to what extent its associated with theoretically relevant factors
has 3 types: concurrent- predictive, convergent, discriminatory

Question 34

random error decreases…

Answer 34

reliability

Question 35

which error type is always wrong?

Answer 35

systematic error