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KIN 209 > Lecture 6 > Flashcards

Lecture 6 Flashcards

1
Q

Within a postpositivist worldview, quantitative strategies are
used to answer research questions and test hypotheses related to:

A
  • determining associations
  • comparing groups
  • developing and testing measures
  • theory verification
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2
Q

5 step process of quantitative design process:

A
  • determining basic questions to be answered
  • determining study participants
  • selecting methods needed to answer questions
  • selecting analysis tools
  • understand and interpret results
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3
Q

When using hypotheses, it is important that they are developed with _____ in mind.

A

theory

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4
Q

The research question is key as it guides the ____ selected.

A

method

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5
Q

An advantage of quantitative research is one can use _____ groups (_____) to potentially make ______ to the _____
population

A
  • smaller
  • sample
  • inferences
  • larger
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6
Q

Population:

A

An entire group or aggregate of people or elements having one or more common characteristic

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7
Q

Sample frame:

A

The group of accessible people that can be connected with about the study

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8
Q

Sample:

A

A sub-group of the population that can be managed by the researcher but will represent the population

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9
Q

Sampling:

A

The process a researcher uses to obtain a sample

from the target population

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10
Q

2 types of sampling:

A
  • probability

- nonprobability

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11
Q

In probability sampling, samples are selected using ____ _____ ensuring that…

A
  • random processes

- every unit in the population has an equal probability of being selected

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12
Q

In probability sampling, the probability of selecting each participant or element is _____.

A

known

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13
Q

In probability sampling, estimating sampling error is _____.

A

possible

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14
Q

In non-probability sampling, how are samples selected?

A

not selected at random

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15
Q

In non-probability sampling, the probability of selecting each participant or element is ______.

A

unknown

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16
Q

In non-probability sampling, it is difficult to say if your sample is… and in turn difficult to…

A
  • representative of population

- generalize findings

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17
Q

Non-probability sampling is ____ expensive and ____ complicated.

A
  • less

- less

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18
Q

4 types of probability sampling:

A
  • simple random sampling
  • stratified random sampling
  • systematic sampling
  • cluster sampling
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19
Q

Simple random sampling:

A
  • every individual has equal opportunity of being selected

- selection of one member does not affect the chances of another member being chosen

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20
Q

Stratified random sampling:

A
  • dividing population elements into subgroups (STRATA) the randomly sample from each
  • ensures representation from each strata
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21
Q

Systematic sampling:

A
  • sampling units are selected in series according to some preset criteria or sequence
  • selection of the 1st element is random, but after this selection is not independent (ex. select every 10th entry)
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22
Q

Cluster sampling:

A
  • participants are randomly selected from a natural occurring group or unit in a population
  • researcher specifies the cluster, which becomes the sampling unit
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23
Q

When to use simple random sampling:

A

anytime

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24
Q

When to use stratified random sampling:

A

when concerned about under representing subgroups

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25
When to use systematic sampling:
when you want to sample every kth element in a ordered set
26
When to use cluster sampling:
when organizing geographically makes sense
27
Advantage of simple random sampling:
- simple to implement | - easy to expalin
28
Advantage of stratified random sampling:
allows oversample of minority groups to ensure subgroup analysis
29
Advantage of systematic sampling:
does not require that you count through all of the elements in the list to find the ones randomly selected
30
Advantage of cluster sampling:
is more efficient than other methods when sampling across geographically dispersed areas
31
Disadvantage of simple random sampling:
requires a sample list to select from
32
Disadvantage of stratified random sampling:
requires a sample list to select from
33
Disadvantage of systematic sampling:
if the order of the elements is nonrandom, there could be systematic bias
34
Disadvantage of cluster sampling:
is usually not used alone, combined with other methods
35
3 types of nonprobability sampling:
- purposive sampling - convenience sampling - snowball sampling
36
Purposive sampling:
- participants purposefully selected because they have specific characteristics the researcher is interested in - not randomly selected = limited generalizability - commonly used with very small sample sizes - common in qualitative research
37
Convenience sampling:
selecting research participants on the basis of being available, accessible, and convenient to the researcher
38
Snowball sampling:
enrolled participants nominate or recruit potential participants who may meet the eligibility criteria
39
When to use purposive sampling:
when you want to examine specific characteristics or experiences
40
When to use convenience sampling:
anytime
41
When to use snowball sampling:
hard to reach populations
42
Advantage of purposive sampling:
easily understood, implement, and explain
43
Advantage of convenience sampling:
easy to do
44
Advantage of snowball sampling:
can be used with no sampling frame
45
Disadvantage of purposive sampling:
limited external validity, likely to be biased
46
Disadvantage of convenience sampling:
very weak external validity, likely to be biased
47
Disadvantage of snowball sampling:
low external validity
48
2 questions when selecting methods needed in quantitative design process:
- how many measurements are being used? | - what types of measures or observations are being used?
49
Selecting methods needed includes identifying:
- variables - measures - design
50
Variable:
an attribute or a characteristic that may vary over time or across cases
51
Types of variables:
- independent - dependent - mediator - moderating - control - confounding
52
Dependent variable (DV):
- The variable that is being affected - it is the outcome being assessed as a result of the independent variable(s) and is the main focus of the study
53
Independent variable (IV):
the variable that is being manipulated (also called treatment variable)
54
Mediator variable:
A variable that is proposed to at least partially explain the relationship between an IV and the DV
55
Moderating variable:
A variable that affect the relationship between two other variables (predictor and outcome)
56
Control variable:
A variable that could influence the outcome or results of the study . . . not the main focus of the study
57
Confounding variable:
An unmeasured variable that is controlled for in the study. It could be the variable could not be measured
58
4 types of measures:
- observational - self-report measures - objective - estimates
59
Observational measures:
recorded by individual observing an action
60
Self-report measures:
an individual reports their own behaviour
61
Objective measures:
taken by instruments or other calibrated devices
62
Estimate measures:
subject matter experts provide best guesses
63
Validity asks...
does the measure do what i is supposed to do?
64
Reliability asks...
does the measure lead to consistent results?
65
3 common types of validity as it relates to measurements:
- construct - content - criterion
66
Construct validity:
how one translates the idea or construct into something real or concrete
67
Content validity:
a check of the operationalization against the relevant content domain of the construct
68
Criterion validity:
the validation of a measure based on its relationship to another independent measure as predicted by your theory of how the measures should behave
69
Reliability:
the repeatability or consistency of a test (or tester) or instrument
70
Reliability is important because any change in scores should reflect a true indication of one's _____ and not....
- ability - change over a short period of time - depend on who is administering the test
71
A valid measurement is _____, but having ______ measurements does not always mean they are valid.
- reliable | - reliable
72
4 general classes of reliability estimates:
- inter-rater or inter-observer reliability - test-retest reliability - parallel-forms reliability - internal consistency reliability
73
Inter-rater or inter-observer reliability:
assess the degree to which different raters/observers give consistent estimates of the same phenomenon
74
Test-retest reliability:
assess the consistency of a measure from one time to another
75
Parallel-forms reliability:
assess the consistency of the results of 2 tests constructed in the same way from the same content domain
76
Internal consistency reliability:
consistency of results across items within a test
77
Shooting-target metaphor: reliable not valid
you are hitting the target consistently but you are missing the centre of the target (it is consistent but not right)
78
Shooting-target metaphor: valid not reliable
- hits are randomly spread across the target - seldom hit bulls-eye but on average are getting the right answer for the group (target) - group estimate is valid, but inconsistent
79
Shooting-target metaphor: neither reliable nor valid
- hits are spread across the top part of the target but are consistently missing the bulls eye - it is consistent and is not right
80
Shooting-target metaphor: both reliable and valid
- consistently hitting the centre of the target | - both consistent and correct

KIN 209 (21 decks)

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