Chapter 5 - Identifying Good Measurement

Question 1

Operationalization/operational definition

Answer 1

• turning a construct of interest into a measured or manipulated variable

Question 2

Conceptual definition/construct

Answer 2

• the researcher’s definition of the variable in question at a theoretical level

Question 3

self-report measures

Answer 3

• recording people’s answers to questions about themselves in a questionnaire or interview

Question 4

observational measures

Answer 4

• recording observable bevahiours or physical traces of behaviours

Question 5

physiological measures

Answer 5

• recording biological data

Question 6

what are the 3 common ways researchers operationalize their variables

Answer 6

self-report
observational
physiological

Question 7

categorical (nominal) variables

Answer 7

• a variable whose levels are categories (ex. male, female)

Question 8

quantitative (continuous) variables

Answer 8

• a variable whose values can be recorded as meaningful numbers (ex. height weight)

Question 9

what are the 3 types of measurement scales for quantitative operational variables?

Answer 9

ordinal
interval
ratio

Question 10

ordinal scale of measurement

Answer 10

• numbers of a quantitative variable represent ranked order
• distance between numerals may not be equal

Question 11

interval scale of measurement

Answer 11

• when numerals represent equal intervals (distances) between levels
• there is no true zero (0 doesn’t mean “nothing”)

Question 12

ratio scale of measurement

Answer 12

• numerals of a quantitative variable have equal intervals and there is a true zero (0 means “none”)

Question 13

Reliability

Answer 13

how consistent the results of a measure are

Question 14

Validity

Answer 14

Whether the operationalization is measuring what it is supposed to measure

Question 15

What are the 3 types of reliability?

Answer 15

test-retest
interrater
Internal

Question 16

test-retest reliability

Answer 16

• a participant will get pretty much the same score each time they are measured with it
• ex. when dealing with a variable such as mood

Question 17

interrater reliability

Answer 17

• consistent scores are obtained no matter who measures the variable

Question 18

Internal reliability

Answer 18

• a participant gives a consistent pattern of answers, no matter how the researchers phrase the question

Question 19

correlation coefficient

Answer 19

• a single number, ranging from -1.0 to 1.0
• indicated the strength and direction of an association between two variables

Question 20

slope direction

Answer 20

• which way the direction of a relationship slopes on a scatterplot
• Positive (up), negative (down), or zero (not at all)

Question 21

strength

Answer 21

• a description of association indicating how closely data points in a scatterplot cluster along a line of best fit drawn through them

Strong: r is close to 1 (strongest positive relationship) or -1 (strongest negative relationship)

Weak: r is close to 0 (no relation)

Question 22

average inter-item correlation (AIC)

Answer 22

• A measure of internal reliability for a set of items; it is the mean of all possible correlations computed between each item and the others
• average of all correlations

Question 23

r

Answer 23

direction and strength of a relationship

Question 24

Cronbach’s alpha (coefficient alpha)

Answer 24

• mathematically combines the AIC and the number of items on a scale
• closer to 1.0, better scale reliability

Question 25

Which type(s) of reliability is relevant for self-report

Answer 25

test-retest internal

Question 26

Which type(s) of reliability is relevant for observational measures

Answer 26

test-retest interrater

Question 27

Which type(s) of reliability is relevant for physiological measures

Answer 27

test-retest interrater

Question 28

Construct validity

Answer 28

- check to make sure a measure is reliable and that it measures the conceptual variables as it was intended

Question 29

face validity

Answer 29

- the extent to which a measure is subjectively considered a plausible operationalization of the conceptual variable in question - ex. hat size has a high face validity as a measurement of head size but low face validity as an operationalization of intelligence

Question 30

content validity

Answer 30

- the extent to which a measure captures all parts of a defined construct - Ex. Conceptual definition of intelligence which contains many aspects such as the ability to reason, plan, solve problems, etc. - content validity requires that the operationalization (ex. Survey) covers questions that attend to all of these specific parts of the variable under study

Question 30

Criterion validity

Answer 30

- evaluates whether the measure under consideration is associated with a concrete behavioural outcome that it should be associated with, according to the conceptual definition

Question 30

Known-groups paradigm

Answer 30

- researchers see whether scores on the measure can discriminate among two or more groups whose behaviour is already confirmed

Question 31

Discriminant validity

Answer 31

- An empirical test of the extent to which a self-report measure does not correlate strongly with measures of theoretically dissimilar constructs - Ex. Depression is not the same as a person's perception of their overall physical health

Question 31

Convergent validity

Answer 31

- An empirical test of the extent to which a self-report measure correlates with other measures of a theoretically similar construct - Ex. A measure of depression should correlate with a different measure of the same construct - depression