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1 2 nd Year Practical: Factorial Designs Dr. Jonathan Stirk Statistical Analysis Using E-Merge, E-Data Aid and SPSS.

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Presentation on theme: "1 2 nd Year Practical: Factorial Designs Dr. Jonathan Stirk Statistical Analysis Using E-Merge, E-Data Aid and SPSS."— Presentation transcript:

1 1 2 nd Year Practical: Factorial Designs Dr. Jonathan Stirk Statistical Analysis Using E-Merge, E-Data Aid and SPSS

2 2 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)

3 3 Individual data Note: some individuals always report pain, others are very resistant. Repeated measure design reduces subject variability. Time levels

4 4 Group data / Interaction Graph

5 5 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.

6 6 Your data For each individual, enter their mean score for each condition/cell into your analysis. Use E-Merge, E-Data Aid & SPSS. If each factor has only 2-levels, no need for pairwise comparisons. Interaction is probably important.

7 7 Example data analysis IVs: – flanker-target separation (distance) 2 levels: near & far – Flanker-target response compatibility 2 levels: compatible & incompatible DV: – Time taken to correctly identify target (RT in milliseconds)

8 8 Design structure for example expt Incompatible Compatible Compatibility FarNear Distance For an individual subject, cell means are an average across a number of trials!

9 9 Merging separate data files Currently you will have a directory which contains your e-prime file and a number of separate.edat files Each subject run will create a single *.edat data file – E.g. *-1-1.edat, *-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

10 10 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

11 11 E-Data Aid Open E-data aid and open the merged file This will contain all the trials for EVERY subject Filter data ready for analysis and output the raw mean data for each participant

12 12 Remove any practise trials from analysis Filter by Procedure[Block]

13 13 Filtering out trials Check the box for the trials that you wish to INCLUDE in the analysis!

14 14 Hide unnecessary columns and filter correct response trials 1 = correct 0 = incorrect

15 15 Choose to analyze correct trials only Choose the name of the slide that participants made responses on to filter for accuracy – E.g. StimDisplay.ACC in the example experiment

16 16 Use Analyze to get raw 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- F_Compatability & – F_distance (or whatever your 2 factor columns have been named) – Data- StimDisplay.RT

17 17 Raw means for subjects StimDisplay.RT:Mean by Subject and F_Compatability, F_distance Mean Stim Displ ay.RT compatible incompatible Subjectfarnearfarnear 1428.93515.50474.69487.21 2596.08444.19450.00455.38 3457.20441.20467.00535.67 SPSS

18 18 E-Data ready for export / copy This analysis provides the MEANS for the 4 conditions (2x2 combinations) you selected This can now be exported or copied into SPSS Just select the data only (not the headings) and press Ctrl-C to copy Open SPSS, create 4 columns and paste data

19 19 Paste into SPSS and rename variables

20 20 Bring conditions over (be consistent!)

21 21 Run analysis! Name the TWO IVs and define the number of levels of each (2) Start with the factor which is highest up in your raw data table e.g. compatibility then distance ADD each in turn

22 22 Results We can see on the basis of only 3 participants that there are NO SIGNIFICANT MAIN EFFECTS for Compatibility or Distance. Also there are no interactions. This is not what we might expect!

23 23 Possible Interaction Graph RT (msecs) nearfar Incompatible Compatible FCE

24 24 And Finally Next week you will be presenting your experiments to the class Each presentation can be given be either 1 or all members of the group Total time of each presentation should be XX minutes You must use POWERPOINT so save file in your user-space or on a floppy disk or USB-drive

25 25 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, 7 th 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

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