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Psych 110 (Stats) > Repeated Measures Experiments > Flashcards

Repeated Measures Experiments Flashcards

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1
Q

Two types of experimental designs

A
  1. repeated measures design
  2. independent groups design
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2
Q

comparing the scores of
individuals in one condition against their scores in
another condition.

A

Repeated Measures Design

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2
Q

comparing the scores of
one group of people taking one condition against the
scores of a different group of people in the other condition

A

Independent Groups Design

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3
Q

change within a
group of individuals, rather than between two groups.

A

Within-subjects studies / designs

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4
Q

other names for repeated measures design

A
  1. Within-subjects studies / designs
  2. Related groups / design
  3. Cross-over studies / design
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5
Q

people undergoing two
different treatments are closely matched, so that the two
groups are not independent, rather they are related.

A

Related groups / design

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6
Q

*strictly speaking, a __________ is a type
of related design; however, it is very rare to encounter
a study where both groups are sufficiently closely
matched.

A

repeated measures design

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7
Q

term mainly used in
medical research than commonly used in psychology.
People cross-over from one group to the other group.

A

Cross-over studies / design

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8
Q

Common Mistakes: _______ and Repeated Measures Designs

when we want to see if people who
were high scorers on one test are also high scorers on
the second test. We are not interested in whether the
scores overall have gone up or down.

A

correlational

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8
Q

Common Mistakes: Correlational and ________

if people on average, score
higher on one occasion than the other.

A

repeated measures

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9
Q

Advantages of Repeated Measures Design

  1. There is no need for many ________.
  2. Each person acts as their own______ matched
    control group.
A
  1. participants
  2. (perfectly)
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10
Q

Disadvantages of Repeated Measures Design

1._______ participants gets better at a task over
time. (solutions: counterbalancing and practice items)

A

Practice effects

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11
Q

Disadvantages of Repeated Measures Design

  1. participants may perceive that a
    dependency exists between two measures, and
    deliberately keep their answers similar when we are
    looking for change. Alternatively, because the
    participants perceive that the researcher is looking for
    change, they might change their answers.
A

sensitization

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12
Q

Disadvantages of Repeated Measures Design

  1. occurs when something about the
    previous condition is “carried over” into the next condition.
A

carry-over-effects

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13
Q

Disadvantages of Repeated Measures Design

A
  1. practice effects
  2. sensitization
  3. carry-over effect
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14
Q

Statistical Tests for Repeated Measures Designs

A
  1. the repeated measures t-test
  2. the wilcoxon test
  3. the sign test
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15
Q

Statistical Tests for Repeated Measures Designs

parametric test for
continuous data.

A

The Repeated Measures t-test

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16
Q

Statistical Tests for Repeated Measures Designs

non-parametric test for ordinal
data

A

The Wilcoxon test

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17
Q

Statistical Tests for Repeated Measures Designs

non-parametric test for categorical data

A

The Sign Test

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18
Q

the most powerful, and most likely to spot
significant differences in data. It can not be used however with all repeated measures data. Data should
also satisfy some conditions before this test can be
used.

A

t-test

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19
Q

Sign test – only deals with data in the form of
categories _____ Easy to understand and
calculate.

A

(nominal data).

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19
Q

Wilcoxon test – deals with all data that can be ordered
________.

A

(ordinal data)

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20
Q

The Repeated Measures t-test

To use this test, we need to make 2 assumptions about our
Data:

  1. The data are measured on a continuous ______ level.
  2. The differences between the two scores are ______
A
  1. (interval)
  2. normally
    distributed.
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21
Q

Common Mistakes: Assumptions of the Repeated Measures t-test

It makes no assumption about the______ of the scores. Only the differences between the scores.

A

distribution

22
Q

Common Mistakes: Assumptions of the Repeated Measures t-test

It is possible to have variables which have highly
______, but which have normally
distributed differences.

A

non-normal distributions

23
Q

Common Mistakes: Assumptions of the Repeated Measures t-test

It makes no assumption about the ______ of the variables.

A

variances

24
Q

Common Mistakes: Assumptions of the Repeated Measures t-test

Given a sufficiently ________, the repeated
measures t-test is robust against violations of both
these assumptions.

A

large sample

25
Q

Common Mistakes: Assumptions of the Repeated Measures t-test

Above sample sizes of approximately ____, the test becomes very robust to violations of distributional
assumptions.

A

50

26
Q

tells us about the likely range of the true value of the score

A

Confidence interval

27
Q

to test the statistical significance of a t-score get the p-value of it to get the score as a result of chance if the NULL is true. For result to be significant, p-value should be____. It should be equal to or _____the alpha level we use for significance testing (alpha levels could be 0.05, 0.01, 0.001 etc.

A

low
less than

28
Q

t-test

p-value of our score should be____ because we assume in the first place that the Null Hypothesis is probably true.

A

low

29
Q

Get the t-critical value and compare the t we got.

  • The t-critical is the t-score which has a p-value equal to the ______ we use. It is relative to the sample size as exemplified by the use of the concept of _______
A

alpha level
degrees of freedom.

30
Q

Get the t-critical value and compare the t we got.

For our t (the t-score we got) to be significant it should be equal to or ______ the t-critical value.

A

more than

31
Q

calculate the confidence interval

The CI tells us the likely range of the score in the population, or if the _____ is measured instead of the sample.

A

population

31
Q

The CI, as an estimate, gives us the possible values the _______ could take or be.

A

TRUE SCORE

32
Q

calculate the confidence interval

In this test, the score we are referring to is the ______(summation of difference scores computed from the two groups/conditions)

A

difference score

33
Q

These range of possible values cover the middle _______of the cases in the distribution.

A

95%

34
Q

Why the middle 95% of cases? Because, the scores within this area, range, or interval are the scores considered to have higher ____ or ____ of occurring compared to the other scores in the distribution.

A

p-values or probabilities

34
Q

This is opposite of what we assume in the first place that if the Null Hypothesis is true, our result should have a ____ or ____ of occurring.

A

low p-value or probability

35
Q

It follows the rule that, if the alternative hypothesis could be true, it should have a_______ of occurring.

A

high probability

35
Q

if our result is statistically significant, it should be contained within the_____

A

CI

36
Q

The Null Hypothesis then should not be contained ______ for our result to be significant.

A

within the CI

37
Q

If it happens that the Null hypothesis is contained in the CI, the result is ______

A

not significant

38
Q

Used when data do not satisfy the assumptions of the repeated measures t-test.

A

The Wilcoxon Test

39
Q

The Wilcoxon Test

The differences are not _______

A

normally distributed

40
Q

The Wilcoxon Test

The measures are ____

A

ordinal.

41
Q

The Wilcoxon Test

Non-parametric test or parametric test

A

non-parametric test

42
Q

The Wilcoxon Test

If data were not measured on an ordinal scale we ______

A

convert them.

42
Q

The Wilcoxon Test

Parametric test – makes inferences about population parameters.
Non-parametric tests use____

A

ranks.

42
Q

Frank Wilcoxon – developed two statistical tests namely the
1.
2.

A
  1. Wilcoxon-rank sum
  2. Wilcoxon signed ranks test.
43
Q

developed two statistical tests namely the Wilcoxon-rank sum and the Wilcoxon signed ranks test.

A

Frank Wilcoxon

43
Q

equivalent to Mann-Whitney test which is easier to calculate.

A

rank sum

44
Q

Thus when we refer to a Wilcoxon test, we refer to the ______ test only.

A

Signed ranks

45
Q

The test statistic for the Wilcoxon Test is known as T (capital T) and is given by whichever is the_____ of these two values.

A

lower

46
Q

Used when we have nominal data with two categories, and have repeated measures data

A

the sign test

46
Q

used to correct for continuity. The z distribution is continuous – that is, any value at all is possible. However, the Wilcoxon T distribution is not truly continuous, because it can only change in steps.

A

continuity correction

47
Q

Easiest statistical test

A

the sign test

47
Q

in the sign test, N is different from in other test.
* The sign test uses N as the ________ from whom there was not a tie.

A

total number of people

48
Q

The test statistic from the sign test is called ___

A

S

Psych 110 (Stats) (9 decks)

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