12_SPF_1

# 12_SPF_1 - Split Plot Factorial Design(SPF-pq(Ch.12 Kirk 2...

This preview shows pages 1–4. Sign up to view the full content.

Split Plot Factorial Design (SPF- p q ) • 2 treatment factors (usually fixed effects) n blocks Æ The set up is similar to RBF- pq . • What are the differences between SPF- p . q and RBF- pq ? – One of the factors is a between-block effect (or between- subject effect, specifically for a repeated measure design). – The researcher is maily interested in • The main effect of within-blocks effect . • The interaction effects of the within-blocks effect and the between-blocks effects. (Ch.12, Kirk) (notation) p is the number of levels for the between-subject factor. q is the number of levels for the within-subject factor. (example - Kirk, p.516) • Dependent measure … vigilant performance • Factor A … the mode of signal presentation Æ a 1 = auditory signal, a 2 = visual signal ( j = 1, 2) • Factor B … four successive hours of monitoring periods Æ b 1 = 1st hour, b 2 = 2nd hour, b 3 = 3rd hour, b 4 = 4th hour. ( k = 1, 2, 3, 4) b 1 b 2 b 3 b 4m e a n s 1 3 4 7 7 5.25 s 2 6 5 8 8 6.75 s 3 3 4 7 9 5.75 s 4 3368 5 s 51 2 04 . 5 s 6 2 3 6 10 5.25 s 7 2459 5 s 82 3 61 15 . 5 a 1 a 2 b 1 b 2 b 3 b 4 mean a 1 3.75 4 7 8 5.69 a 21 . 7 53 5 . 05 . 0 6 mean 2.75 3.50 6.25 9.00 ( ABS summary Table) ( AB summary table) The entry is Y ijk The entry is jk Y

This preview has intentionally blurred sections. Sign up to view the full version.

View Full Document
Estimated Marginal Means of MEASURE_1 HOURS 4 3 2 1 Estimated Marginal Means 12 10 8 6 4 2 0 SIGNAL 1.00 2.00 Estimated Marginal Means of MEASURE_1 SIGNAL 2.00 1.00 12 10 8 6 4 2 0 HOURS 1 2 3 4 (model) () () () i j k j ij k j k k Y =µ+α +π +β + αβ + βπ Where µ … grand mean α j … effect the j th level of factor A π i ( j ) … effect of i th block within factor A (error term for A ) β k … effect of the k th level of factor B ( αβ ) jk AB interaction effect ( βπ ) ki ( j ) B x Block effect within factor A (error term for B and A x B )
(Sum of squares and Degrees of freedom) (ANOVA table) SS df A = 3.125 p -1 ±= ±1 BL = 9.375 p ( n -1)±= ±6 B = 194.5 q ±3 AB = 19.375 ( p -1)( q -1) B x BL = 9.125 p ( n q -1)±=±18 Sourse SS df MS F p-value Between Blocks A 3.125 1 3.125 2 0.207 BL 9.375 6 1.562 Within Blocks B 194.5 3 64.833 127.88 p < .001 AB 19.375 3 6.458 12.74 p < .001 BxBL 9.125 18 0.507 (See Kirk, p.517 for E ( MS ) formulas) (SPSS Analysis) • Use the repeated measure procedure (GLM Æ

This preview has intentionally blurred sections. Sign up to view the full version.

View Full Document
This is the end of the preview. Sign up to access the rest of the document.

## This note was uploaded on 11/27/2011 for the course EDF 5402 taught by Professor Thomasbaldwin during the Fall '09 term at FSU.

### Page1 / 11

12_SPF_1 - Split Plot Factorial Design(SPF-pq(Ch.12 Kirk 2...

This preview shows document pages 1 - 4. Sign up to view the full document.

View Full Document
Ask a homework question - tutors are online