Special Tests for Three-way Designs: Interaction Effects and Contrasts - Prof. Colleen F. , Exams of Psychology

Information on applying two-way tests and contrasts to collapsed data from higher way designs, specifically three-way designs. It discusses single df contrasts on marginal means, individual cell means, pooled two-way matrices, simple main effects, and partial interactions. The document also introduces the concept of simple interaction effect and provides examples of sscp@rir and sscp@pr. The handout concludes by stating the results of the interaction effect between period and cue for rir and pr.

Typology: Exams

Pre 2010

Uploaded on 09/02/2009

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Psych 610 Handout #22, p. 1
Prof. Moore
SPECIAL TESTS FOR THREE (AND HIGHERWAY) DESIGNS
I. All two-way tests and one-way tests discussed previously can be applied to collapsed (pooled)
data from higher way designs.
* Can run single df contrasts on marginal means
* Can run single df contrasts on individual cell means
* Can run two-way single df contrasts on pooled two-way matrices (i.e., CB, CP, BP)
* Can run simple main effects on pooled two-way matrices
* Can run partial interactions on pooled two-way matrices
II. Can extend notions of two-way and partial interaction contrasts to 3 (and higher) way designs if
it makes sense.
III. New test: simple interaction effect
Asks whether there is an interaction between two factors, say CP, at a particular level of a third
factor, say B.
Let’s compute SSCP@RIR =
541250
40
000,650,21
40
41002200
@][
22
==
+
=RIRC
589500
20
000,790,11
20
150020002300500
@][
2222
==
+++
=RIRP
000,637
10
000,370,6
10
10001300....900100
@][
2222
==
+++
=RIRCP
125,496
80
6300
@][
2
==RIRT
SSCP@RIR = [CP] – [C] – [P] + [T] = 2375
MSCP@RIR = 2375/3 = 791.67
52.1
83.520
67.791 ==F
ns.
Conclude: For RIR’s, there is no interaction between period and
cue. A-V is better than A at all levels by about the same
amounts.
pf2

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Psych 610 Handout #22, p. 1 Prof. Moore SPECIAL TESTS FOR THREE (AND HIGHERWAY) DESIGNS I. All two-way tests and one-way tests discussed previously can be applied to collapsed (pooled) data from higher way designs.

  • Can run single df contrasts on marginal means
  • Can run single df contrasts on individual cell means
  • Can run two-way single df contrasts on pooled two-way matrices (i.e., CB, CP, BP)
  • Can run simple main effects on pooled two-way matrices
  • Can run partial interactions on pooled two-way matrices II. Can extend notions of two-way and partial interaction contrasts to 3 (and higher) way designs if it makes sense. III. New test: simple interaction effect Asks whether there is an interaction between two factors, say CP, at a particular level of a third factor, say B. Let’s compute SSCP@RIR = 541250 40

[ ] @

2 2 = =

C RIR =

[ ] @

2 2 2 2 = =

P RIR =

[ ] @

2 2 2 2 = =

CP RIR =

[ ] @

2 T RIR= = SSCP@RIR = [CP] – [C] – [P] + [T] = 2375 MSCP@RIR = 2375/3 = 791.

  1. 52
  2. 83

F = =

ns. Conclude: For RIR’s, there is no interaction between period and cue. A-V is better than A at all levels by about the same amounts.

Handout #22, p. 2 Now do the same for SSCP@PR 470 , 500 40

[ ] @

2 2

C PR =

[ ] @

2 2 2 2

P PR =

[ ] @

2 2 2 2

CP PR =

[ ] @

2 T PR= = SSCP@PR = [CP] – [C] – [P] + [T] = 27, MSCP@PR = 27,000/3 = 9,000 F = 9,000/520.83 = 17.28 p <. Conclusion: The difference between A and AV cues is not the same at all periods for PR’s. (We see visually, it begins small, increases to max at time period = 24, then drops off.) Note: SSCP@RIR + SSCP@PR = 2375 + 27,000 = 29, SSCP + SSCPB = 21187,5 + 8187.5 = 29,