Two types of experimental designs
comparing the scores of
individuals in one condition against their scores in
another condition.
Repeated Measures Design
comparing the scores of
one group of people taking one condition against the
scores of a different group of people in the other condition
Independent Groups Design
change within a
group of individuals, rather than between two groups.
Within-subjects studies / designs
other names for repeated measures design
people undergoing two
different treatments are closely matched, so that the two
groups are not independent, rather they are related.
Related groups / design
*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.
repeated measures design
term mainly used in
medical research than commonly used in psychology.
People cross-over from one group to the other group.
Cross-over studies / design
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.
correlational
Common Mistakes: Correlational and ________
if people on average, score
higher on one occasion than the other.
repeated measures
Advantages of Repeated Measures Design
Disadvantages of Repeated Measures Design
1._______ participants gets better at a task over
time. (solutions: counterbalancing and practice items)
Practice effects
Disadvantages of Repeated Measures Design
sensitization
Disadvantages of Repeated Measures Design
carry-over-effects
Disadvantages of Repeated Measures Design
Statistical Tests for Repeated Measures Designs
Statistical Tests for Repeated Measures Designs
parametric test for
continuous data.
The Repeated Measures t-test
Statistical Tests for Repeated Measures Designs
non-parametric test for ordinal
data
The Wilcoxon test
Statistical Tests for Repeated Measures Designs
non-parametric test for categorical data
The Sign Test
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.
t-test
Sign test – only deals with data in the form of
categories _____ Easy to understand and
calculate.
(nominal data).
Wilcoxon test – deals with all data that can be ordered
________.
(ordinal data)
The Repeated Measures t-test
To use this test, we need to make 2 assumptions about our
Data:
Common Mistakes: Assumptions of the Repeated Measures t-test
It makes no assumption about the______ of the scores. Only the differences between the scores.
distribution