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Research Design Human Movement 2032 > WEEK #6 - research methods > Flashcards

WEEK #6 - research methods Flashcards

1
Q

what is measurement ?

A

is the assignment of a number of a number to a characteristic of an object

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2
Q

what does measurement allow ?

A

measurement allows the characteristic in question to be compared between objects

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3
Q

in addition to physical objects, what else foes measurement deal with ?

A

intangible characteristics

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4
Q

what are some examples of psychological construct variables that cannot be directly measured ?

A

intelligence, self-esteem, depression, pain, anxiety, etc.

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5
Q

what is the term used to describe variables that cant be directly measured ?

A

constructs

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6
Q

why cant constricts be observed directly ?

A

as they represent tendencies to think, feel or act in certain ways

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7
Q

what is the conceptual definition of a construct ?

A

describes the behaviours snd internal processes that make up that construct and how it relates to other variables

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8
Q

what does conceptually mean ?

A

having a clear and complete conceptual definition of a construct t is a prerequisite for good measurement. it allows you to make sound decisions about exactly how to measure the construct

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9
Q

what does operationally mean ?

A

defines how precisely a variable is to be measured and ensures that all researchers are measuring the construct using the same method

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10
Q

define operational ?

A

in order to be able to accurately measure a variable or construct an operational definition is required and clearly defining the operational definition is important as there may be multiple operational definitions for a variables and constructs

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11
Q

what is covering operations ?

A

when various operational definitions converge on the same construct and have scores closely related to each other it is evidence that the operational definitions are measuring the c obstruct effectively

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12
Q

what are the three types of measure ?

A
  • self-report measures
  • behavioural measures
  • physiological measures
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13
Q

what is self-sport measures :

A

participants report their own thoughts, feelings, and actions

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14
Q

what are examples of self-sport measures ?

A

PHQ9, GAD7, SCAT 5 symptom evaluation

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15
Q

what is behavioural measures ?

A

participants behaviour is observed and recorded

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16
Q

what are examples of behavioural measures ?

A

allow children to play in a room and observe/record them

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17
Q

what is physiological measures ?

A

involve recording any of a wide variety of physiological processes

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18
Q

what are examples of physiological measures ?

A

HR, BP, SPO2

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19
Q

what are the types of data ?

A

continuous variables and discrete variables

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20
Q

what are continuous variables ?

A
  • can assume any value
  • example : distance, time, force
  • accuracy of the data is dependent on the measuring device
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21
Q

what are discrete variables ?

A
  • limited to certain numbers (typically whole numbers or integers)
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22
Q

are clinical variables continuous or discrete ?

A

clinical variables are discrete (when making a discrete diagnosis a person either has the condition or they do not)

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23
Q

how many categories can data be grouped into ?

A

4

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24
Q

what are the four categories that data can be grouped into ?

A
  • nominal
  • ordinal
  • interval
  • ratio
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25
Q

define nominal :

A
  • mutually exclusive categories of subjects
  • no qualitative differentiation between categories
  • subjects are classified into one of the categories then counted
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26
Q

give an example of nominal :

A

students were classified as male or female then the number in each category was counted

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27
Q

define ordinal :

A
  • also referred to as rank order scale
  • quantitative ordering of the variables but does not indicate the magnitude of the relationship or difference between them
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28
Q

give an example of ordinal :

A

the top 3 finishers of a race are ranked first, second and third but there is no indication of how much faster first place was to second place and second place to third place

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29
Q

define interval :

A
  • equal units of measurement with the same distance between each division of the scale
  • there is no absolute zero point
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30
Q

give an example of interval :

A

fahrenheit scale, 60 degrees is hotter than 10 degrees but 100 degrees is not tie as hot as 50 degrees since 0 degrees doesn’t not represent a complete absence of heat

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31
Q

define ratio :

A
  • equal units of measurement between each division of the scale
  • zero represents an absence pf value
  • since all units are proportional comparisons are appropriate
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32
Q

give and example of ratio :

A

all measurements of distance, force and time

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33
Q

what are the four levels of measurement ?

A

1) nominal
2) ordinal
3) interval
4) ratio

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34
Q

how many of the 4 levels of measurement are category labels ?

A

all 4

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35
Q

how many of the 4 levels of measurement are rank order ?

A
  • 3 of the 4
  • ordinal, interval, ratio
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36
Q

how many of the 4 levels of measurement are equal intervals ?

A
  • 2/4
  • interval and ratio
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37
Q

how many of the 4 levels of measurement are true zero ?

A
  • 1/4
  • ratio
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38
Q

define reliability ?

A
  • refers to the consistency of a measure
  • does the measure consistency reflect changes in what it purports to measure
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39
Q

with reliability, what are we looking that the measure is stable across ?

A

time and circumstance

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40
Q

how many types of reliability are there ?

A

3

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41
Q

what are the three types of reliability ?

A

1) test-retest reliability
2) internal consistency
3) inter-reader reliability

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42
Q

define test-retest reliability :

A

consistency over time

43
Q

define internal consistency :

A

consistency of responses across the items on a multiple-item measure

44
Q

define inter-rater reliability :

A

consistency between different observers in their judgements

45
Q

how do we measure reliability ?

A
  • split half correlation (this involves splitting the items into two sets, such as the first and second halves of the items or the ben- and odd- numbered items
  • cronbach’s a (the mean of all possible split-half correlations for a set of items)
46
Q

define validity :

A

validity is the extent to which the scores from a measure represent the variable they are intended to

47
Q

how many types of validity are there ?

A

4

48
Q

what are the four types of validity ?

A

1) content validity
2) criterion validity
3) discriminant validity
4) face validity

49
Q

define face validity :

A
  • is the extent to which a test is subjectively viewed as covering the concept it purports to measure. It refers to the transparency or relevance of a test as it appears to test participants.
  • face validity is at best a very weak kind of evidence that a measurement method is measuring what it is supposed to
50
Q

define content validity :

A
  • the extent to which a measure “covers” the construct of interest
51
Q

TRUE OR FALSE

content validity is usually assessed quantitatively

A

FALSE

content validity is NOT usually assessed quantitively
(assessed by carefully checking the measurement method against the conceptual definition of the construct)

52
Q

define criterion validity :

A
  • the extent to which people’s scores on a measure are correlated with other
    variables (known as criteria) that one would expect them to be correlated with.
  • A criterion can be any variable that one has reason to think should be correlated
    with the construct being measured, and there will usually be many of them
53
Q

what are three points of criterion validity ?

A

1) concurrent validity
2) predictive validity
3) convergent validity

54
Q

describe concurrent validity :

A

When the criterion is measured at the same time as the construct

55
Q

describe predictive validity :

A

When the criterion is measured at some point in the future (after the construct has been
measured)

56
Q

describe convergent validity :

A

other measures of the same construct

57
Q

what is discriminant validity ?

A

The extent to which scores on a measure are not correlated with measures of variables that are conceptually distinct.

58
Q

what is efficiency ?

A

is the data precise and reliable, at the lowest possible cost ?

59
Q

what is generality ?

A

can the method be applied successfully to a wide range of phenomena

60
Q

how many measurement error are there ?

A

5

61
Q

what are the 5 measurement errors ?

A
  • parallax error
  • calibration error
  • zero error
  • damage
  • limit of reading of the measurement device
62
Q

define parallax error :

A

incorrectly sighting the measurement

63
Q

define calibration error :

A

if the scale is not accurately drawn

64
Q

define zero error :

A

if the device doesn’t have a zero or isn’t correctly
set to zero

65
Q

define damage :

A

if the device is damaged or faulty

66
Q

define limit of reading of the measurement :

A

the measurement can only be as accurate as the smallest unit of measurement of
the device

67
Q

how many types of error are there ?

A

3

68
Q

what are the three types of errors ?

A

1) gross errors
2) systematic errors
3) random errors

69
Q

what are gross errors ?

A

Gross Errors mainly covers the human mistakes in reading instruments and recording and calculating measurement results

70
Q

what are systematic errors ?

A
  • instrumental errors
  • environmental errors (external and environmental factors)
  • observational errors (inaccurate readings, conversion error)
71
Q

(systematic errors) what are instrumental errors ?

A

shortcoming, misuse, measurement accuracy

72
Q

(systematic errors) what are environmental errors ?

A

external and environmental factors

73
Q

(systematic errors) what are observational errors ?

A

inaccurate readings, conversion error

74
Q

what are random errors ?

A

errors caused by disturbances about which we are unaware

75
Q

what is the contingency table of hypothesis testing ?

A

sample result, population result, Ha true and Ho true

76
Q

what is Ha true ?

A

difference between measures does exist

77
Q

what is Ho true ?

A

difference between measures does not exit

78
Q

TRUE OR FALSE

type 1 and type 2 are causes of error

A

TRUE

79
Q

what are type 1 causes of error ?

A
  • measurement error
  • lack of random sample
  • alpha value too liberal
  • investigator bias
  • improper use of one tailed test
80
Q

what are type 2 causes of error ?

A
  • measurement error
  • lack of sufficient power (N too small)
  • alpha value too conservative
  • treatment effect not properly applied
81
Q

define bias :

A
  • factors that operate on a sample that make it unrepresentative of the population
  • often subtle and may go undetected
  • sufficiently large samples will eliminate unknown factors that
    cause bias
82
Q

what are expectancy effects of measurement bias :

A
  • confirmation bias
  • recording baises
  • halo effect
  • social desirable bias
83
Q

what is confirmation bias ?

A

finding what you were looking for

84
Q

what is recording bias ?

A
  • might be more accurate to call these ‘recall biases (occur when experimenters rely on imperfect records - e.g., their memory of their
    interview(s) with the participants)
  • availability heuristic
    (more ‘graphic’ information is easier to recal land ‘vividness problem’ )
  • primacy / recency effect (tendency to remember the first and last pieces of information presented during an interview)
85
Q

what is the halo effect ?

A
  • when non-experimental variables affect experimental measures
  • very common in subjective appraisal of individual differences
    (e.g., well-groomed individuals judged to be conscientious * e.g., attractive individuals judged to be healthy)
86
Q

what it social desirable bias ?

A
  • participant selectively reports ‘positive’ information to the
    experimenter
  • impression management
87
Q

what are the four expectancy effects of ‘participant types’ :

A
  • the “good” participant
  • the “bad” participant
  • the “faithful” participant
  • the “apprehensive” participant
88
Q

define the “good” participant :

A

participant behaves in a way that ‘confirms’ the experimenters hypothesis

89
Q

define the “bad” participant :

A

participant behaves in a way that ‘disconfirms’ the experimenter’s hypothesis

90
Q

define the “faithful” participant :

A

the participant follows experimenter’s instructions scrupulously

91
Q

define the “apprehensive” participant :

A

participant is unusually concerned with experimenter’s evaluation of him/her

92
Q

what is the expectancy effects of the pygmalion effect ?

A

when the experimenter causes real change in the participants due to (presumably unconscious) changes in his/her behaviour during the experiment

93
Q

what is the expectancy effect of the Hawthorne effect ?

A
  • studied the performance effects of changing a variety of working conditions
  • is usually used to refer to a change in a positive direction
94
Q

what is the expectancy effects of the halo effect ?

A
  • when used to describe behavioural changes within an experiment, is usually referring to ‘uncontrolled novelty of treatment’
  • when the novelty of any new treatment is likely to cause an individual to demonstrate significant improvement in the short-term
  • on average, tends to evaporate within 8 weeks of treatment presentation
95
Q

what is the expectancy effects of the placebo effect ?

A
  • the ‘placebo effect’ is actually a cluster of determinants:
  • ‘spontaneous remission’ or ‘maturation’ (sometimes, symptoms just improve on their own, naturally)
  • non-specific effects of treatment
    (the generalized effect of ‘being in treatment’)
  • ‘re-interpretation’ of outcome measures
    (temporary improvement confused with cure & cognitive re-appraisal of symptoms)
96
Q

what are some other expectancy effects ?

A

biosocial experiment cues and psychosocial experimenter cues

97
Q

how do you reduce expectancy effects ?

A
  • standardize experimenter-participant interaction
  • use blinding techniques
  • use deception (active or passive deception)
  • convince participant that you can detect lying
98
Q

talk about safeguards against misleading studies :

A
  • competition for research funding (only “the best” projects are funded)
  • results are disseminated in peer-reviewed journals (experts decide what is worthy of publication)
  • replication, replication, replication! (guards against Type I error and “invisible bias”)
99
Q

who funds sources ?

A
  • private industry (e.g. drug companies)
  • government agencies
  • philanthropic organizations
  • special interest groups
100
Q

what are some problems with peer review ?

A
  • non democratic
  • “error of central tendency”
  • assumes that reviewers are consistent, competent, and timely in their reviews
101
Q

describe the non-democratic problem with peer review :

A
  • limited pool of reviewers
  • generally consists of individuals with similar research objectives (i.e. individuals in competition with the scientist)
  • selection of reviewer’s at editors discretion
    (decision to accept/reject largely in the hands of one person)
102
Q

describe the “error of central tendency” problem with peer review continued :

A

moderate viewpoints more fundable/publishable than more novel viewpoints

103
Q

what is the “wastebasket effect” ?

A

non significant findings often are not published

Research Design Human Movement 2032 (11 decks)

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