Standardisation

Question 1

Define psychometrics and psychological testing

Answer 1

It’s the science of psychological measurement; psychological tests are a measuring device or procedure designed to measure psychology-related variables

Question 2

List 5 different types of psychological tests and provide examples

Answer 2

1. Mental ability (IQ tests, memory, vocabulary, spatial ability);
2. Achievement (educational, course assessments, competence, experimental performance measures);
3. Personality-type (no correct answer; assessing traits);
4. Interests and attitudes (vocational, social psych questionnaires);
5. Neuropsychological tests (memory, psychomotor coordination, abstract thinking, IQ, personality, etc)

Question 3

What are the four key assumptions behind psychological tests?

Answer 3

1. People differ on traits
2. These traits are measurable
3. These traits are relatively stable over time
4. These traits relate to actual behaviour

Question 4

What are the advantages of standardisation?

Answer 4

It helps us interpret what the scores mean relative to the appropriate sample of people; raw scores alone are uninformative.

Question 5

Explain what norm and normative sample are

Answer 5

Normative sample is a standardised score relative to a sample of people (reference sample/standardised sample); the norm is the data they yield

Question 6

What issues might we need to consider when recruiting a standardised sample?

Answer 6

A bigger sample is more likely to lead to an accurate and stable representation of the population (but
stability doesn’t guarantee representativeness); may need equal ratio of males to females, same age, socio-economic and educational distribution; same geographic origins of the population

Question 7

Define stratified cluster sampling

Answer 7

Deliberately recruiting representatives to get particular ratios of subgroups (as opposed to random
sampling)

Question 8

If stratified cluster sampling fails or is not possible, what’s another option?

Answer 8

Weighting (e.g. If male to female ratio is uneven, count each female as 1.5 people, and each male as .67 of a person)

Question 9

Why is the normal curve (aka the Laplace-gauss curve) important in psychology?

Answer 9

If we can assume something has a normal curve, then knowing only the mean and standard deviation can tell us how someone’s score compares with everyone else

Question 10

When does a distribution come closer to a normal curve?

Answer 10

When a sample is larger, and with a wider range of things measured

Question 11

When a sample is normally distributed, what is the mean equal to?

Answer 11

Both median and mode (so 50% of people are above/below the mean)

Question 12

In a normal distribution, what percentage of scores are +/-1 SD around the mean?;
What about +/-2 SDs?

Answer 12

68%;

95%

Question 13

What’s the general definition of cognitive impairment and what’s notable about the properties of this
definition?

Answer 13

An IQ of below 2 SDs below the mean (less than 70); this means “mentally retarded” is always in comparison with the rest of the population (it’s not absolute)

Question 14

Why is it convenient for our distributions to be normal?

Answer 14

We can do more powerful (parametric) statistical tests, and makes scales more comparable

Question 15

What are the different strategies we can use to make a skewed distribution normal?

Answer 15

Do a non-linear transformation to make it more normal (e.g. take the square root or logarithm); or redesign the measure if possible (e.g. change wording of items)

Question 16

Does performing a non-linear transformation change the rank order of scores?

Answer 16

No, it just stretches some bits of the scale more than others

Question 17

Why do we use standard scores?

Answer 17

Makes the interpretation simpler; anchors the mean and SD of the scale; can potentially compare performance across different scales

Question 18

What are the means and SD of:
z score?;
T score?;
IQ score?

Answer 18

Z score: mean = 0, SD = 1;
T score: mean = 50, SD = 10;
IQ score: mean = 100, SD = 15

Question 19

How do we covert a raw score into a z score?

Answer 19

z = X - Xbar / SD

Question 20

How do we covert a z score into a T score?

Answer 20

T = z(10) + 50

Question 21

How do we covert a z score into an IQ score?

Answer 21

IQ = z(15) + 100

Question 22

Does calculating a T score change the shape of the distribution?

Answer 22

No, it is a linear transformation (also avoids negative numbers)

Question 23

A person scores 70 on a test, where the mean is 85, and SD is 20. You have created a standardised
scale where the mean is 100 and the SD is 50. How would you find their score according to your
scale?

Answer 23

z = (70 - 85)/20 = -0.75;

-0.75(50) + 100 = 62.5

Question 24

Give 3 examples of linear transforms, and 3 of non-linear transforms?

Answer 24

Linear: z, T and IQ tests;

Non-linear: logarithms, square roots and percentile ranks

Question 25

How do we work out a percentile rank?

Answer 25

Calculate the z score, then look up a table of the standard normal distribution (larger portion for positive and smaller portion for negative)

Question 26

What are the advantages of using percentile ranks?;

Disadvantages?

Answer 26

Easy to understand for laypeople and easier to calculate; Confusion between percentile rank and percentage correct; location on scale means different things - ranks close to 50 include a smaller range of scores and are bunched up (those near 0 or 100 are more spread out)

Question 27

What are the properties of the Stanine scale?

Answer 27

Often used in school tests; has 9 divisions - each .5 SDs wide; the middle band (5) is from -.25 - +.25 SDs; 20% of people are in this middle band; Neale analysis of reading uses Stanines

Question 28

How can we create a narrative report from raw test scores or vice versa?

Answer 28

By coding certain scores into qualitative labels (e.g. 7 = outstanding) or coding labels into quantitative data (e.g. Outstanding = 7)

Question 29

Describe how norm-referenced scoring works

Answer 29

Score is relative to a norm; protected from the possibility that the test may be easier or harder; will yield a good distribution (can discriminate between good and bad test-takers); score is affected if the norm changes (disadvantaged if in a smart cohort)

Question 30

Describe how criterion-referenced scoring works

Answer 30

Score is relative to an absolute score (set standard); unaffected if the norm changes; can set absolute standards based on what people can actually do; score is affected by test difficulty; more likely a skewed distribution (fails to discriminate between people); possible for everyone to pass or to fail

Question 31

Why is converting your percentage score to a grade (1-7) a non-linear transformation?

Answer 31

It changes the shape of the distribution because different grades cover different ranges