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Lab K
An exercise in experimental design and implementation
Between-subjects design Within-subjects design- each person in the lab would
be assigned to one of the four ‘treatments’ using random allocation (eg. rolling a fair die and ignoring two of the faces, generating random numbers in minitab and ignoring all but digits 1, 2, 3 and 4, etc.)
- Randomisation is used so that there are no systematic differences between the people allocated to different treatments – i.e. it attempts to control for potential confounding variables
- each person in the lab would be asked to perform the experiment under each of the conditions, i.e. four times
- randomization would be used to assign participants to a particular order of the treatments, thereby counterbalancing the design to minimize the potential order-effects acting as a confounding factor
Between-subjects design Within-subjects designAdvantages and disadvantages+ only requires each participant to do
the experiment once, thereby saving time
+ potential order effects (eg. fatigue, practice, crossover effects) are avoided and do not need to be controlled for in the design
+ the subsequent analysis is straight forward, as there are four independent groups to compare
+ the randomization is relatively straight forward
- would require a larger number of participants to get adequate numbers in each treatment group
Advantages and disadvantages- requires each participant to do the
experiment four times, thereby needing a lot of time
- introduces potential order effects (eg. fatigue, practice, crossover effects) which the design should carefully consider in order to minimize the potential effects (i.e. lag between experiments)
- the subsequent analysis is complex, involving the analysis of repeated measures
+ more powerful to detect treatment differences, since effects of individuals are controlled
+ would require a relatively small number of participants to get reliable results for each treatment level
Suggested design and why
Given our limited numbers in the lab group, we would favour the within-subjects design, notwithstanding the additional work involved in the randomization and the analysis.
To make a Latin square…
1. Create a random order of the levels, (e.g. BACD for a four-level IV)
2. Sequentially number the levels in this random order starting with 1. (e.g. B=1, A=2, C=3 and D=4)
3. To create the first order in the Latin square, put the last number/level in the 3rd position, (e.g. 1, 2, 4, 3). If we had more than four levels, N say, then every subsequent unevenly numbered position (e.g. 5, 7, and so on) would have one less than the previous unevenly numbered position as shown in the following table.
Ordernumber
1 2 3 4 5 6 7 8 9 10
Level 1 2 N 3 N-1 4 N-2 5 N-3 6
Labeling of the treatment levels in the random order
1 = C 2 = D 3 = B 4 = A
Latin Square of labels Latin square of treatments
1 2 4 3 Order 1 C D A B
2 3 1 4 Order 2 D B C A
3 4 2 1 Order 3 B A D C
4 1 3 2 Order 4 A C B D
Random allocation to orders1 4 11 2 21 4 31 2
2 1 12 1 22 1 32 3
3 2 13 4 23 3 33 1
4 2 14 2 24 3 34 2
5 3 15 3 25 2 35 1
6 3 16 2 26 4 36 2
7 2 17 4 27 1 37 3
8 4 18 3 28 1 38 1
9 1 19 4 29 4 39 1
10 3 20 1 30 1 40 1
Series 1
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Series 3
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ferret
Series 4
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gerbil
Series 1
baboon
peanut
locust
carpet
glider
fleece
almond
cymbal
jackal
bikini
chisel
pepper
budgie
sandal
coyote
Series 2
badger
raisin
maggot
cooker
rocket
jacket
banana
fiddle
jaguar
blazer
hammer
potato
canary
sarong
donkey
Series 3
beaver
tomato
slater
fridge
sledge
jumper
cherry
guitar
lizard
blouse
roller
radish
condor
shorts
ferret
Series 4
cougar
walnut
spider
heater
sleigh
mitten
orange
violin
monkey
braces
shovel
sprout
cuckoo
slacks
gerbil