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Expected Mean Squares

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Results can be derived as we need for the two-stage nested model ... P(G)xT. s2PS 5s2GS 3s2PT 15 SSGTik2/3. GxT. s2PS 10s2S. S(T) s2PS 3s2PT 10s2S 30 STk2/3 ... – PowerPoint PPT presentation

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Title: Expected Mean Squares


1
Expected Mean Squares
  • Crossed and nested factorial models with fixed
    and random factors
  • Results can be derived as we need for the
    two-stage nested model
  • Algorithms for SS, df, and EMS (though we will
    cover only df and EMS)

2
Rules for df
  • The replication subscript is nested for the error
    term
  • There are 3 types of subscripts
  • Live Present and not nested
  • Dead Present and nested
  • Absent Absent from term (only used for SS)
  • DfProduct of levels of each dead subscript and
    (levels-1) of each live subscript

3
Example 1
  • Hospitals are randomly selected to test surgical
    methods (M). At each hospital (H), doctors (D)
    are randomly selected to treat randomly selected
    patientseach doctor uses all surgical methods
    with n patients.
  • YijklmHi Mj HMijDk(i) MDjk(i)el(ijk),
    i1,,a
  • j1,,b k1,,c l1,,n

4
Example 1
Source Df
H I-1
M J-1
D(H) I(K-1)
MD(H) I(J-1)(K-1)
Error IJK(n-1)
Total IJKn-1
5
Example 1
I J K n
R F R R
i j k l Component
Hi 1 J K n sH2
Mj I 0 K n SMj2/(J-1)
HMij 1 0 K n sHM2
Dk(i) 1 J 1 n sD2
MDjk(i) 1 0 1 n sMD2
el(ijk) 1 1 1 1 s2
6
Example 1
Source EMS
H s2 Jn sD2JKn sH2
M s2 n sMD2 Kn sHM2IKn SMj2/(J-1)
HM s2 n sMD2Kn sHM2
D(H) s2Jn sD2
MD(H) s2n sMD2
Error s2
7
Example 2.1
  • Two groups of 5 randomly selected students each
    are tested on knowledge of 4 sentence types.
    Every student answers the same 3 randomly
    selected sentences of each type.
  • YijklmGi Pj(i) TkSl(k) GTjk
  • PTjk(i) GSil(k) PSjl(ik)

8
2 5 4 3
F R F R
i j k l Component
Gi 0 5 4 3 SGi2
Pj(i) 1 1 4 3 s2P
Tk 2 5 0 3 STk2/3
Sl(k) 2 5 1 1 s2S
GTik 0 5 0 3 SSGTik2/3
PTjk(i) 1 1 0 3 s2PT
GSil(k) 0 5 1 1 s2GS
PSjl(ik) 1 1 1 1 s2PS
9
Source EMS
G s2PS 5s2GS 12s2P 60 SGi2
P(G) s2PS 12s2P
T s2PS 3s2PT 10s2S 30 STk2/3
S(T) s2PS 10s2S
GxT s2PS 5s2GS 3s2PT 15 SSGTik2/3
P(G)xT s2PS 3s2PT
GxS(T) s2PS 5s2GS
P(G)xS(T) s2PS
10
Example 2.2
  • Discard the interactions involving random effects
  • YijklmGi Pj(i) TkSl(k) GTjk
  • el(ijk)

11
Example 2.2
2 5 4 3
F R F R
i j k l Component
Gi 0 5 4 3 SGi2
Pj(i) 1 1 4 3 s2P
Tk 2 5 0 3 STk2/3
Sl(k) 2 5 1 1 s2S
GTjk 0 5 0 3 SSGTik2/3
el(ijk) 1 1 1 1 s2
12
Example 2.2
Source EMS
G s2 12s2P 60 SGi2
P(G) s2 12s2P
T s210s2S 30 SGi2/3
S(T) s2 10s2S
GxT s2 15 SSGTik2/3
Error s2
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