Week 8

Question 1

Define a repeated-measures design and what is it sometimes called?

Answer 1

Sometimes called “within-subject design”, the dependent variable is measured two or more times for each individual in a single sample.

Question 2

Explain how a repeated-measures design differs from an independent-measures design.

Answer 2

Single sample as opposed to two or more samples.

Question 3

Define a matched-subjects design.

Answer 3

Each individual in one sample is matched on a particular variable with an individual in the other sample.

Question 4

Explain how a matched-subjects design differs from a repeated-measures design.

Answer 4

Repeated measures designs have perfect matching, matched-subject have partial matching.

Question 5

Explain how a matched-subjects design differs from an independent-measures design.

Answer 5

Each sample is matched on variables rather than being two or more randomly selected groups.

Question 6

Describe the data that are used for the repeated-measures t statistic.

Answer 6

Uses D scores rather than X scores.

Question 7

Describe the hypotheses for a repeated-measures t test.

Answer 7

H₀: μD = 0 and H₁: μD ≠ 0.

Question 8

What are D scores?

Answer 8

The difference between X₁ and X₂ (before and after treatment).

Question 9

What is MD? (D is subscript)

Answer 9

Mean of D scores.

Question 10

What is μD?

Answer 10

The mean of difference scores for the whole population.

Question 11

What is the t-statistic formula for a repeated measures design?

Answer 11

t = MD - μD/sMD

Question 12

What is sMD? (M and D are subscript)

Answer 12

The estimated standard error of MD.

Question 13

The related-samples t statistic requires two basic assumptions, what are they?

Answer 13

1. The observations for treatment condition must be independent.
2. The population distribution of difference scores (D values) must be normal (or large).

Question 14

What is the estimated Cohen’s d for repeated measures designs?

Answer 14

d = MD/sD

Question 15

How does the r² test (better known as ω²) differ for independent measures t tests and repeated measures t tests?

Answer 15

It doesn’t, it is always r² = t²/t² + df.

Question 16

What is the confidence interval formula for repeated measures t tests?

Answer 16

μD = MD ± tsMD

Question 17

Larger samples produce a larger value for the t statistic (farther from zero) and increases the likelihood of rejecting H₀, TRUE OR FALSE?

Answer 17

TRUE.

Question 18

Larger variance produces a smaller value for the t statistic (closer to zero) and reduces the likelihood of rejecting H₀, TRUE OR FALSE?

Answer 18

TRUE.

Question 19

How does variance in D scores indicate consistency of treatment?

Answer 19

Little variance in D scores indicates that the treatments have approximately the same effect on all subjects.

Question 20

What are the advantages of repeated measures designs?

Answer 20

1. Requires fewer subjects.
2. Allows observation of change over time.
3. Removes individual differences.
4. Significantly less variance.

Question 21

What are the disadvantages of repeated measures designs?

Answer 21

1. Order/sequencing effects.

2. Time factors.

Question 22

What is a nuisance variable?

Answer 22

A type of extraneous variable that increases the variability within participants in an experiment.

Question 23

What are the two main types of nuisance variables?

Answer 23

1. Participant.

2. Environment.

Question 24

How do you control participant nuisance variables?

Answer 24

1. Repeated measures designs with counter balancing.
2. Matched-designs (variables can be overlooked and missed however).
3. Independent group design (requires larger groups).

Question 25

How do you control environmental nuisance variables?

Answer 25

Difficult, but one solution is to hold them constant.

Question 26

How do you calculate sMD?

Answer 26

sMD = sD/square root of n.