Ch 6 - Measurement Flashcards

(41 cards)

1
Q

3 distinctions between qualitative and quantitative measurement techniques

A
  1. TIMING - think about variables and convert them into specific actions during a planning stage that occurs before and is separate from gathering and analyzing data
    QUAN - measurement occurs before data collected
    QUAL - occurs during data collection
  2. DATA THEMSELVES - quantitative - numbers - represents abstract ideas, qualitative - sometimes numbers more often spoken words, actions, sounds, symbols, physical objects, images - develop flexible ongoing processes to measure the data that leave those data in various shapes sizes and forms.
  3. HOW STYLES MAKE LINKAGES between data and concepts -
    QUAN - reflect on concepts before gathering data, measurement techniques that bridge concepts and data.
    QUAL - reflect on ideas before data collection - develop most of concepts during data collection - reexamines and reflects simultaneously and interactively
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2
Q

conceptualization

A

is the process of taking a concept and refining it by giving it a conceptual or a theoretical definition

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3
Q

conceptual definition

A

is a definition in abstract, theoretical terms

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4
Q

operationalization

A

links a conceptual definition to a specific set of measurement techniques or procedures, the concepts operational definition

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5
Q

Guidelines for Coming Up with a Measure

A
  1. Remember the conceptual definition
  2. Keep an open mind
  3. Borrow from other
  4. Anticipate difficulties
  5. Do not forget your units of analysis
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6
Q

Measurement process for QUAN

A

First conceptualization
Operationalization
Application of operational definition or measuring to collect the data

abstract ot concrete

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7
Q

conceptual hypothesis QUAN

A

A type of hypothesis in which researcher expresses variables in abstract, conceptual terms, and expresses the relationship among variables in a theoretical way

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8
Q

empirical hypothesis QUAN

A

a type of hypothesis in which the researcher expresses variables in specific terms and expresses the association among the measured indicators of observable

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9
Q

Conceptualization QUAL

A

QUAL - refine rudimentary working ideas during the data collection and analysis process - develop new concepts, formulate definitions for concepts, consider relationships among concepts, clear explicit definitions abstract - determined BY THE DATA

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10
Q

OPERATIONALIZATION QUAL

A

forms conceptual definitions out of rudimentary working ideas that they used while making observations or gathering data

instead of going from conceptual def to measurement operations - describe how specific observations and thoughts about the data contributed to working ideas that are the basis of conceptual definitions and theoretical concepts

operationalization - after the fact description

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11
Q

How to improve reliability

A

Conceptualize clearly

Increase level of measurement - more precise

Use multiple indicators of a variable

Pretests, pilot studies, replication

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12
Q

measurement validity

A

how well the conceptual and operational definitions mesh with each other

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13
Q

Content validity

A

is the full content of a definition represented in a measure

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14
Q

Criterion Validity

A

measurement validity that relies on some independent outside verification

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15
Q

Criterion validity > concurrent validity

A

relies on a pre-existing and already accepted measure to verify the indicator of a concept

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16
Q

criterion validity > predictive validity

A

measurement validity that relies on the occurrence of a future event or behavior that is logically consistent to verify the indicator of a concept

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17
Q

Qualitative researchers more interested in BLANK than validity

A

authenticity - fair honest and balanced account of social life from the POV of someone who lives it everyday

Credibility and transferability- external validity

18
Q

internal validity

A

no errors internal to the design - eliminating alternative explanations

19
Q

external validity

A

generalize from experimental research to settings or people that differ from the specific conditions of the study

20
Q

statistical validity

A

achieved when an appropriate statistical procedure is selected and the assumptions of the procedure are fully met

21
Q

Levels of measurement

A

an abstract but important and widely used idea.

Some ways in which a researcher measures a concept are at a higher more refined level and others are crude or less precisely specified

22
Q

Continuous variables

A

Infinite number of values or attributes that flow along a continuum - can be divided into smaller increments

23
Q

Discrete variables

A

relatively fixed set of separate values or variable attributes - contain distinct categories - religious affiliation

24
Q

Nomial

A

Difference among categories

discrete
religion

25
ordinal
difference plus the categories can be ordered or ranked - likert discrete
26
Interval
Everything the first two do and can specify the amount of distance between categories - celsius arbitrary 0s continuous
27
Ratio
everything all the other levels do plus there is a true 0 continuous
28
Mutually exclusive attributes
individual or case fits into one and only one attribute of a variable religion - can only only fit into one category
29
exhaustive attributes
all cases fit into one of the attributes of a variable - every possible situation is covered - listing all religions
30
Index/scales
both produce ordinal or interval level measures of a variable information about variables and possible to assess the quality of measurement
31
Index
summing or combining of many separate measures of a construct or variable
32
Scale
Like an index is an ordinal interval or ratio measure of a variable expressed as a numerical score. most are ordinal
33
two purposes of scales
1. help in the conceptualization and operationalization processes - shows fit between indicators and construct 2. scaling produces quantitative measures and can be used with other variables to test hypotheses
34
standardization
the procedure to statistically adjust measures to permit making an honest comparison by giving a common basis to measures of different units
35
concepts
the things studied
36
measurement * the process moves from the general to the specific:
conceptual definition * operational definition * identify indicators (variables) related to the operational definition * we first arrive at a conceptual definition and then identify measures of those concepts; e.g. MBM vs before and after-tax low income
37
quantitative data is more prone to _________ problems
validity
38
qual data is more prone to _________ problems
reliability
39
regardless of the level of measurement, every variable must have two qualities:
the attributes must be exhaustive * the attributes must be mutually exclusive
40
* Index:
typically just adds/averages items * e.g. a political participation index would just add together how many these things a person did * vote * attend candidate debates * donate money to political party * sign on lawn during election problem? Not all of the items in this index should be treated equally
41
* Scales:
a technique for properly measuring the intensity of items in relation to each other; most are ordinal level