Flashcards in MEASUREMENT AND METHOLOGY Deck (142):

1

## MEAUREMENT AND METHODOLOGY

### - assessment behaviours, attitudesm mental constructs personality, and mental health

2

## Intelligence

###
- mental construct specifically defined

- intelligence is NOT IQ

- IQ is score of inteligence

- unlikely that IQ captures all intelligence

3

## Alfred Binet

###
- developed IQ and first IQ test (Binet Scale) = mental age/chronological age x 100

- Intelligence stops developing after age 16

4

## Mean IQ of Americans

###
- is 100

- SD = 15 or 16

5

## Stanford Binet Intelligence Scale

###
- revised version of Binet's intelligence test

- best known predictor of future academic achievement

6

## Lewis Terman

###
- from standford university and revised the Binet Intelligence Scale

- studies of children with higher IQ are better adjusted (gifted children)

7

## Weschler Adult Intelligence Scale (WAIS)

###
- most commin IQ test for dults

- organized by subtests

8

## Wescler Intelligece Scale for Children (WAIS-R)

### - for children age 6-16

9

## Wechsler Preschool and Primary Scale of Intelligence (WPPSI)

### - for children age 4-6

10

## Goodenough Draw a Man Test

###
- notable for cros cultural application an simple directions to draw the very best picture

- are marked via detial and accuracy, not talent

11

## IQ correlates mostly with who?

### - biological parents and socioeconomic status of parents (income or job type)

12

## John Horn and Cattell

### - found fluid intelligence decines with old age and cyrstaliized intelignece does not

13

## Robert Zajonc

###
- relationship between birth order and intelligence

- firstborns more intellignece than 2nd

- greater spaces between children = higher intelligence

14

## Charles Spearman

### - general factor in human intellignece called "g"

15

## Achievement test

###
- measure how well you know a particular subject

- measure past learning

16

## Aptitude test

###
- meaure your innate ability

- predict future perofmrance

17

## Objective test

### - subects can't make own answers, are already structure

18

## Structure test

###
- more objectively scored than projective tests

- most are self-reported (but still subject to response bias)

19

## Q-sort, Q-measure techniques

###
- process of sorting cards into normal distrbution

- each card with a personality statmente and neutral ones and place at the hump and definind or undefining cards are put into the sides

20

## Mineesota Multiphasic personality Inventory (MMPI)

###
- OG for mental illnes but now a peronality meaure

- T/F questions

- items to discriminate between different disorders

- high validity becau of items and 3 validity scales (lying, carelessness, faking)

21

## California Personality Inventory (CPI)

### - use for more "normal" and less clinical groups

22

## Myer-Briggs Type Indicator (MBTI)

###
- derived from Jung's personality theory (archetypes)

- 2 answer per question then given 4 letter personality type

1) introvert/extravert

2) sensing/intuition

3) feeling/thinking

4) judgment/perception

23

## Julain Rotter

### - creater internal/external locus of control

24

## Projective tests

###
- subjects to create own answer through expression of conflicts, need, impulses

- content is interpreted by administrators

- some may be score objectively

25

## Rorschach Inkblot Test

###
- subject desrcibe what they see in 10 inkblot

- complex scoring

- questionable validity

26

## Thematic Apperception Test (TAT)

###
- cards of interpersonal scences are shown and subject tells story of each card to reveal personality

- used to measure need for achievmenet

- needs, press, persnology are terms with test

27

## Reosenweig Picture Frustration (p-F) stud

###
- cartoons where 1 person is frustrating the other

- subject ask to describe how frustated person responds

28

## Word Association Test

###
- used in conjucnction with free association tecniques

- word called out, subject says next word that comes to mind

29

## Rotter Incomplete Sentence Blank

###
- similar to word association

- subject finish sentences

30

## Draw a Person Test

### - asks subject to draw a person of each sex and tell a story about them

31

## Beck Depression Inventory (BD)

### - not to diagnose depression but for severity of depressive symptoms and track course of symptoms

32

## Empirical-keying or criterion keying approach

###
- constructing assessment instruments invovles selection of items that discriminate between various groups

- response determines if person is in particular group or not

- e.g. Strong-Campbell Interest INventory

33

## Vocational Test

### - what extent individual's interest and strengths match those already found by professionals in particualr job field

34

## Lie detector test

### - measure arousal of sympathetic nervous system which becomes stimulated by lying (and anxiety)

35

## walter Mischel

###
- critical of personality trait-theory and personality tests in general

- felt situations decided actions (not traits)

36

## Anne Anastasi

### - researched intelligence in relation to performance

37

## F-scale or F-ratio

### - measurement of facism or authoritarian personality

38

## Bayley Sclaes of Infant Developent

###
- not intelligene tests

- mesure senory/motor development of infants to identify mentally retarded children

- poor predictors of later intelligence

39

## Research design

###
- how research attempts to examine hypothesis

- differnt quetions = different approachs

- some are called more scientific than others

40

## Scientific approach to psychology involves (3)

###
1) testable hypothesis

2) reporductible experiment can be replicated

3) operationalized defintiion of concept under study

41

## Field study

###
- takes place in naturalistic setting

- less control over enviornment

- generates more hpyothesis than can be proved

42

## Experimental design

###
- takes place in controlled setting

- draw causal conslusions from experiment

43

## IV

### - manipulates IV by applying it in experimental or treatment condition by withhodling if from the control condition

44

## DV

### - does not control the dependent variable but examineshow IV effects the DV

45

## Confounding variable

###
- attempts to minimize or eliminate confounds

- variables in environment that might also affect DV and blue effect of IV on DV

46

## Sample or subgroup

###
- drawn from population bc is impossible to include all members

-sample must be representative of population and unabiased

47

## Random sampling

###
- applied to achieve representative population and unbias sample

- every member of population has an equal chance of getting chosen

48

## Conviencance sampling

### - used when random sampling is not possible e.g. a group of psych students

49

## Stratified sampling

###
- to make results more generalizable then convienanc sampling

- aims to match emographic characteritcs of sample to demographics of population

50

## Longitudinal design

###
- studying same objects at differnt points in lifespand and provides better, mored valid result than most other methods

- time consuming

51

## Cross-sectional design

###
- different subjects of different ages are compared

- faster, easier than longitudinal

52

## Cohort-sequential design

### - combines longiudeninal and cross-sectional approaches

53

## Within-subjects

### - test same person at multiple time points and looks at chnges within person

54

## Between-subject design

### - compares 2 groups of ppl at the same time point

55

## Quasi-experimental esign

### - compares 2 groups of people but design is used when it is not feasible/ethical to use random assignment e.g. you cannot assign one group to smoke for 20 years

56

## Double-blind

### - experiments when neither subject nor experimenter knowns whether subject is assigned treatment or control

57

## Placebo

### - inactive substance disgused as substance in control group

58

## Predicitve value

### - degree to which IV can predict DV

59

## Generalizability

### - degree to which results from experiment can be applied to population and real world

60

## Acquiescence

###
- when ppl agree with opppsing statment

- "careless" responding

61

## Cohort effects

### - effect that might result when group is born and raised in particular time period

62

## Demand characteristic

### - subject act in way that they think experimenter wants or expects

63

## Experimenter bias

###
- researchers see what they want to see

- AKA rosenthal effect

- minimized in double blind experiment

64

## Rosenthal effect AKA

### - AKA experimenter bias

65

## Hawthorne effect

###
- subjects alter their behaviour because they know they are being observed

- applies to workers altering their behaviour for the same reason

66

## Nonequivalent control group

### - problematic type of control group when an equivalent canot be isolated

67

## Placebo effect

### - subjects behave different because thy think they have recieved treatment substance or condition

68

## Reactance

###
- attitude change in response to feeeling that options are limited

- e.g. someone is set on a type of ice cream flavour when they find out it is sold out

69

## Selective attrition

###
- when subjects that drop out of an experiment are different from those that reamin

- remaining sample is no longer random (morality effects)

70

## Social desirability

### - when subjects do and say what they think puts them in a favourable light

71

## Illusory correlation

###
- when a relationship is inferred when there is actually is none

- e.g. people insist a relationship exists between physical and personality characteristics depsite evidence tht no such relationship exits

72

## Meta-analysis

###
- study that mathematically comvines and summarize overall effects of research findings for topic

- calcualte 1 overall effect size

- needed when conflicting results are found

73

## Insittuional review board (IRB)

###
- all studies have to pass ethical standards

- all subjects are provided with risk and benefit of being in study and then sign a consent form

- Milgram experiment (electric shocks) was the catalyst for higher ethical standards in psychological research

74

## Statistics

### - process of repreenting or analyzing numerical data

75

## Descriptive statistics

###
- organize data from a sample by showing it in a meaningful way

- do not allow conclusions to be drawn beyond by the sample

76

## Percentiles

###
- most common on standardized test

- shows position in whole group

77

## Frequenecy distrubutions

###
- how data in study looked

- might show how often different variables appeared

78

## Nominal variables

###
- descriptive bames

- no order or relationship among variables but grouping

79

## Ordinal variables

###
- implies order

- nothing else is known (equal spacing not assumed)

80

## Interval variables

###
- implies order and equal spacing

- do NOT include a real zero

- 0 is arbiturary and does not signify absence of temperature

81

## Ratio variable

### - have order, equal intervals and a real zero e.g. age - incrases by a year, increases and has an absolute 0

82

## Graphs

### - used to plot zero

83

## Frequency polygon

###
- plotted points connected by lines

- often used to plot continuous varaibles

84

## Histogram

###
- consists of vertical bars in which the sides of vertical bars touch

- for discrete varisbles that have clear boundaries

- interval variables where there is order

- bars lined up in order

85

## Bar graph

###
- vertical lines in historgram but o not touch

86

## Measures of central tendecny

###
- where on a number line the data set falls in general

- 3 types of central tendecny (mean, mode, median)

87

## Mean

###
-average

- affected by high scores (outliers)

88

## Standard error of the mean

### - calculate how "off" the mean might be in either direction

89

## Median

### - find the middle of the set

90

## Mode

### - most frquenctly occuring value

91

## Variability

### - additional informtion to central tendency by telling you how the scores are spread out overall

92

## Range

###
- basic measure of variability but subtracting lowest to highest value

- is the spread

93

## Variance/standard deviation

###
- how much variation there is among the number in distrubution

1) how much each score differs from mean

2) square each deviation

3) add all deviations = sum of square

4) divided by n = variance

4) take square root of variance = standard deviation

- large = highly disperesed

94

## Normal distribution

###
- AKA bell curve

- larger sample = greater chance of bell curve

- unimodal (one hump) --> mean, median and mode are all equal

95

## z-scores

###
- normal distribution

- how many standard deviations a score is from the mean

- usually -3 to 3

96

## t-score

###
- transformation of z-score

- mean = 50

- SD = 10

= t= 10(Z)+50

97

## Standard normal distribution

###
- same thing as normal distribution

- mean = 0

- SD = 1

98

## Correlations

###
- part of statistics but neither purely descriptive nor purely inferential

- show relationships NOT causlity between variables

99

## Positive correlation

###
- simple and linear

- one increases, so does other variable

100

## Negative correlation

###
- simple and liner

- as one variable goes down, the other goes up

101

## Cuvilinear correaltion

###
- not simple and linear

- looks like a curved line e.g. arousal and performance

102

## Zero correlation

### - no relationship between the variables

103

## Person r correlation coefficient

###
- way of numerically calculating and expressing correlations

- range from -1 to +1

- -1 = perfect negative correlation

- +1 = perfect positive correlation

- 0 = no relationship

- strength of relationship is how close it is to -1 or +1

104

## Spearman r correlation coefficient

###
- another correlation and used when the data in form of rank

- used to determine the line of linear relationships

105

## z scores with what percentile rank?

### 34:14:2

106

## Regression

###
- step above simple correaltions

- looks are the variance accounted for

107

## Statitical regression

### - identify relatioship between 2 variables and makes predictions about 1 variable based on another varible

108

## Inferential statistics

### - allows generalizability from sample to population

109

## Statistics

### - numbers that descirbe the sample

110

## Parameters

### - numbers that describe the popultion

111

## Significance

###
- if numbers that desribe the sample are describing real differences or pattern rather than random variable

- if significant, research can generalize the same findings to population

112

## Test of significance

###
- hoping to reject the null hypothesis (hypotheis that no real differences exisit)

- test of significant shows that statiscs were significant and that you can reject the null hypotheis

113

## Alpha level

### - a significance level used by most of

114

## Type 1 error

###
- incorrectly reject the null hypothesis

- a false positive

115

## Type 2 error

###
- incorrecty accept the null hypothesis

- a flase negative

116

## T-tests

###
- compare means of 2 different groups to see if groups are truely different

- analyze continuous data

- can not test for more than 2 groups

117

## Chi-square

###
- when n are classified into categories or cells

- tells us whether the groups are significantly different in size

- look at patterns or distributions (not means)

- analyze categorical or discrete data

- can assess "goodness of fit" - whether pattern is what would be expected

118

## Categorical/discrete data

### - data that has been countd rather than measured so limited to positive and whole numbers (usually)

119

## ANOVA

###
- popular because of flexibility

- analyze differences among means of continuous variables but it more flexible because more than 2 groups

120

## 1 way ANOVA

### - tests whether the means on one outcome or DV are significantly diffferent across groups

121

## 2 way ANOVA

### - test the effects of 2 independnet variables or treatment conditions at once

122

## Factorial analysis of variance

###
- used when an experiment involves more than one IV

- can separate the effects of different levels of different beariables

- split each IV into levels which yield combinations

123

## Main effects (factor analysis)

### - the effect of IV on DV

124

## Interaction effects (factor analysis)

###
- combine the IV

- effects of DV change depending on the level of IV

125

## Analysis of Covariance (ANCOVA)

###
- tests whether at least 2 roups co-vary

- can adjust for preexisting differences between groups

126

## Linear Regression

###
- allows use of correlation coefficients in order to predict one variable from another variable

- meaure relationship but don't describe the relationship

- use correlational data to make predictions based on a line fit with the least-squares method

127

## Creating tests with statistics

### - ensure that measures are on target

128

## Standardized test

### - used to create norms and tried out on huge groups of people

129

## Criterion-reference test

### - measure master parituclar subject e.g. final exam

130

## Domain-referenced test

### - measure less-defined properties e.g. intelligence and need be checked for reliability and validity

131

## Reliability

### - how stable the measure is

132

## Test-re-test reliability

###
- measured by the same individual taking the same test more than once

- high test re-test = person would et the same core each time

133

## Split-half reliability

###
- comparing an individuals' performance on 2 halves of th same test

- reveals internal consistency of test

134

## Item analysis

###
- increase internal consistency

- analyze how large group responded to each item on the meaure

- weeds out problematic items and replaced with better questions with discriminatory value

135

## Validity

### - how well the test mesures a construct

136

## Internal validity

### - the extent to which the different items within a measure "hang together" and test the same thing

137

## External validity (4)

###
- extent to which test measure what is intends to measure

1) concurrent

2) construct

3) content

4) face

138

## Concurrent validity

###
- whether scores on new measure positively correlate with other measures known to test the same construct

- AKA cross validation

139

## Construct validity

### - whether the test really taps he abstract concept being measured

140

## Content validity

### - whether the content of the test covers a good sample of the construct being measured (not just part of it)

141

## Face validity

### - whether the test items simply look like they measure the construc

142