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2nd Year Practicals: Statistical Analysis Using E-Merge, E-Data Aid and EZ-ANOVA

Dr. Jonathan Stirk

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Repeated Measure Design-(Fully-Within Subjects)

Research Hypothesis: Does coping strategy influence pain?

Dependent Variable: Report of pain level 0..50 (0=no pain, 50=excruciating).

Independent Variables:– Coping strategy: Concentrate on Pain vs. Avoidance. – Time hand has been in ice water (3 levels: 30, 60, 90 sec).

8 subjects participate in all conditions (“repeated measures 2 x 3 design”)

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Individual data

0

5

10

15

20

25

30

35

40

45

1 2 3 4 5 6

Mary

Jane

Jill

Jean

Corey

Pam

Jennifer

Jersey

Concentrate Avoid

Individual Effects

Note: some individuals always report pain, others are very resistant. Repeated measure design reduces subject variability.

Time levels

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Group data / Interaction Graph

Group Effects

0

5

10

15

20

25

30

1 2 3

Time

Pa

in R

ati

ng

Concentrate

Avoidance

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ANOVA

Source SS df MS F P

Coping 46 1 46.02 1.87 0.213

related Error 172 7 24.54

Time 2140 2 1070.02 36.69 0.001

related Error 408 14 29.16

Coping*Time 288 2 144.02 21.09 0.001

related Error 96 14 6.83

Subjects 1055 7 150.74

• No main effect of coping strategy.

• Main effect of time: more time = more pain.

• Interaction: Avoidance better for short periods, but worse with longer intervals.

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Your data

For each individual, enter their mean score for each condition/cell into your analysis.

Analyse target present and target absent data separately. (only use 2-WAY ANOVA).

Use E-Merge, E-Data Aid & EZ-ANOVA / SPSS. If each factor has only 2-levels, no need for pairwise

comparisons. Interaction is probably important.

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Example data

Target Present DataStat 1 2 3 4

Familiar UnfamiliarSubject 4 Items 8 Items 4 Items 8 ItemsAlex 341 455 325 509Bob 423 515 401 501Corey 464 501 452 561Dave 505 532 485 578Eve 455 469 422 521Fred 431 533 461 559Gary 412 534 423 611Harriet 380 460 345 501

Repeat for Target Absent data (stat 5,6,7,8 data)

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Merging separate data files

Each subject run will create a single *.edat data file – E.g. ‘interlv-1-1.edat’, ‘interlv-2-1.edat’ etc.

Merge these into 1 large file using E-Merge This produces a merge file (*.emrg) You should open this merge file using E-Data

Aid

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Select Unmerged files (check they are all from the same experiment)

Click MERGE and name the merged file with something sensible

Ctrl-Left click will also choose each file

E-Merge

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E-Data Aid

Open E-data aid and open the merged file

You want to run separate analyses on the target present and target absent data, so choose filter (then checklist) and choose stat 1-4 or 5-8 (or whatever stat values are relevant for your exp’t if you have renumbered your cell conditions)

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Filtering Data

Once the filter is set your analysis will be limited to the Target Present or Absent subgroups

You may also want to analyse only RTimes from “correct” trials so filter using ‘STIMULUS.ACC’=1 and look at % errors too

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Analyse Data

To get the means for your data use the ANALYZE option in E-Data Aid (Looks like a calculator)

This will open the window seen on the right

– Row- Subject– Column- Stat– Data- Stimulus.RT

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E-Data ready for export / copy

This analysis provides the MEANS for the 4 conditions you selected

This can now be exported or copied to the clipboard ready to be analysed using EZ-ANOVA (or SPSS if you know how)

Just select the data and press Ctrl-C to copy

You may want to analyse median scores rather than means – double click on the data summary in previous window to alter

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EZ-ANOVA

Name your 2 factors (IV’s) e.g. Familiarity & Set Size (use max of 8 characters for factor & level names)

Set levels, choose number of rows (subjects)

Make sure you choose repeated measures design if it was

SetSz

4 8

FamiliarityFam 1 2

Unfam 3 4

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Results

ANOVA Table

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Interaction Graph

Target Present Trials

400

500

600

4 items 8 items

Set Size

RT

(m

s) Familiar

Unfamiliar

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EZ-ANOVA Plot

FamUnfam

500

600

700

800

Interaction Graph

4 8

Set Size

RT (msec)

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ANOVA help

For additional help on related (within-subjects) ANOVA see

– Keppel, G., Saufley, W.H.,Tokunaga, H. (1992) Introduction to Design and Analysis. (in library)

– Sprinthall, R.C.(2003). Basic Statistical Analysis, 7th Edition.– Howell, D. (1992). Statistical methods for psychology. – Dancey, C.P & Reidy, J. (2002). Statistics without maths for

psychology. – Or any other major stats text