Prism Lab Stats
Dr. Roger Newport
&
Laura Condon
Room B47. Drop-In Sessions: Tuesdays [email protected]://www.psychology.nottingham.ac.uk/staff/rwn/Teaching/C82MPR.html
How a standard experiment might look
Condition 1PreExp (e-prime?)Post
Condition 2PreExp (e-prime?)Post
We only need to record the last few pre-exposure and the first few post-exposure in each manipulation
132
-6-5-3
} 2.0
} -4.7
Man1
Pre
Man1
Post
Man2
Pre
Man2
Post
2.0 -4.7 1.8 -3.2S1
S2
Sn
Manipulation 1
Table of means for ANOVA
Two-factor ANOVA
2-way repeated measures Analysis of Variance.
Each subject participates in ALL conditions
We could stick it all into a….
What does the 2-factor ANOVA test for?
• Differences between levels of Factor A(“main effect of A”)
• Differences between levels of Factor B(“main effect of B”)
• Other differences(“interaction”)
• So the 2-factor ANOVA involves computing three separate F ratios - three independent hypothesis tests!
What would we do if the interaction was significant?
Unplanned comparisons
Accuracy
-20-15-10
-505
101520
Pre Post
Exposure
mm YM1
YM2All possible comparisons
M1pr v M1poM1pr v M2prM1pr v M2poM1po v M2prM1po v M2poM2pre v M2po
What would we do if the interaction was significant?
Unplanned comparisons
Accuracy
-20-15-10-505
101520
Pre Post
Exposure
mm YM1
YM2All possible comparisons
M1pr v M1poM1pr v M2prM1pr v M2poM1po v M2prM1po v M2poM2pre v M2po
What would we do if the interaction was significant?
Unplanned comparisons
Accuracy
-20-15-10-505
101520
Pre Post
Exposure
mm YM1
YM2All possible comparisons
M1pr v M1poM1pr v M2prM1pr v M2poM1po v M2prM1po v M2poM2pre v M2po
alpha = .0083
Planned comparisons
Accuracy
-20-15-10-505
101520
Pre Post
Exposure
mm YM1
YM2
What do we really want to know?What were our hypotheses?Why did we do the experiment?
All possible comparisons
M1pr v M1poM1pr v M2prM1pr v M2poM1po v M2prM1po v M2poM2pre v M2po
alpha = .05
Simplifies analysis
Reduces risk of type I errors (& don’t have to adjust alpha level)
Interpretation is easy as each comparison is derived from a specific hypothesis
No tricky interactions to interpret
Only have results that you are interested in
Advantages of planned comparisons:
Disadvantages: SPSS does not (easily) do the comparisons we need
Accuracy
-20-15-10-505
101520
Pre Post
Exposure
mm YM1
YM2
The outcome we predicted
Show there is no difference here
But that there is a difference here
How do we perform a planned comparison?
Not just a t-test because we must take into account the variability of the whole model
How do we do it in SPSS when SPSS doesn’t do it?
Testing the planned comparisons
F ratios need to be calculated for each comparison and for that we need the mean square
the mean square is calculated by:
FAcomp =MSAcomp
MSS/A
Do a 2x2 ANOVA…
…to get the residual mean square from the whole model
Then do a one way ANOVA on the comparison in question…
…to get the mean square for the comparison
FAcomp =MSAcomp
MSS/A
Divide one by the other to get the F ratio
FAcomp =MSAcomp
MSS/A
Do the same for the other comparison
Critical F's for comparisons use the degrees of freedom for the numerator and the denominator of the F-ratio.
In my example there are 1 and 7 degrees of freedom for this comparison.F(1, 7) = 10.51, p= 0.0142
Bung these values into an online F ratio calculatore.g. http://faculty.vassar.edu/lowry/tabs.html#f
Or use a book of tables
You can’t trust anything you find online, so test the calculator with these values: F = 5.99; Numerator = 1; Denominator = 6. You should get a p value of 0.05
Note that this is different to both the 2 way interaction and the 1 way significance values
Evaluating the planned comparison’s null hypothesis
Now then, although you have run three ANOVAs you do not have to report this.
If you specify planned comparisons there is no need to describe or report the omnibus.
You do, however, have to state that you are performing planned comparisons and give the rationale/hypothesis for them early doors (i.e. at the end of the introduction)
General
Why
Specific
Specific
Why
General
What/How
Outcome
Prism adaptation
Other variable
Hypotheses and predictions
Method - replicability
Results F[1,5] = 2.4, p<0.05SE bars on graphs
Describe outcomes
Why you got those outcomes
What it all meansFuture research
Refer to literature
Refer to literatureFollow the guidelines on the prism web page
What is known about PA(that is relevant to the study)
What is known about our manipulation (that is relevant)
How one should affect the other
Hypothesis / brief method of testing
ResponseTarget
Measurement
Make good use of pictures to describe your experimental setup
time
If people were right handed (for example) say how you know
Make sure it is prelicable
F[1,5] = 2.4, p<0.05SE bars on graphs
Collation of means etc.
Type of analysis (not package used)
0
5
10
15
20
Pre Post
Phase
erro
r (m
m)
two legsone leg
Figure 1: blah de blah de blah
Give direction of effects
Give means in table or graph, not both
No need to report the omnibus
Come to a conclusion
If suggesting further research give concrete examples of how to go about it
and how it would have a bearing on your results?
What are the implications of your results?How do they add to the literature?
What do they mean?Do they fit previous research - why?
What were the main results?
There are further instructions about how to present your reports on the course web page. Ignore them at your peril (by which I mean: ignore them and lose marks)
DoNot Use TextThatIsTooSmall
Do not put too much information on one page as this will make it really really difficult for your audience to take in both what is on the screen and what you are saying. They won’t have time to read it and they will start to lose interest. At the same time do not simply read out exactly what is on the page because your audience will be able to do that for themselves. You should try to give the impression that you know what you are talking about and above all do not mumble
And they can remind you what to say next, but they can also look rubbish if not done very well
Bullet points are good
They emphasise important points
If you choose a fancy backgroundMake sure you can still read the text
If you choose a fancy backgroundMake sure you can still read the text
If you choose a fancy backgroundMake sure you can still read the text
If you choose a fancy backgroundMake sure you can still read the text
If you choose a fancy backgroundMake sure you can still read the text
Top Related