STRIP PLOT DESIGN AND MULTILOCATIONS

Erlina Ambarwati

SPLIT BLOCK DESIGN (STRIP PLOT)

Utamanya digunakan dalam bidang pertanian.2 faktor, A dan B, diacak pada main plot.A diacak dengan mendatarB diacak dengan vertikalMisalnya A: penggenangan

B: penyemprotan herbisidaA & B diconfoundedkan

a1 a2 a4 a3 a0

b3

b2

b0

b1

Model Linear

Tabel Anova

ijkjkikkijjiijkY

SR df SS EMS (fixed treat)

Blok

A

Error 1

B

Error 2

A*B

Error 3

r-1

a-1

(r-1)(a-1)

b-1

(r-1)(b-1)

(a-1)(b-1)

(r-1)(a-1)(b-1)

SSR

SSA

SSE1

SSB

SSE2

SSAB

SSE3

Total rab-1 SStot

2

22

22

222

22

222

e

ABe

e

Be

e

Ae

ra

raab

rabb

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Penghitungan semua JK (SS) seperti pada simple split plot. Kecuali untuk errornya.

ABEBEARtoterror

BRperror

kip

ARperror

ijp

SSSSSSSSSSSSSSSS

SSSSSSSS

CFYa

SS

SSSSSSSS

CFYb

SS

213

22

2

11

1

2

.

2

.

1

1

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Konsentrasi

Rep

Genangan

1 2 3 4 5 6

ITSR

10,39,89,0

9,710,19,6

11,211,010,8

10,810,410,1

10,510,69,8

9,99,511,0

184,1

IITSR

11,810,710,1

10,311,610,9

12,111,912,1

12,311,811,0

11,811,710,3

10,610,19,2

200,3

IITSR

10,29,59,7

10,110,79,3

11,610,811,2

11,29,99,6

10,610,510,4

10,39,410,3

185,3

91,1 92,3 102,7 97,1 96,2 90,3 569,7

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44,345,493,03,381,219,1205,917,3617,3651,6046

45,43,319,1294,19

94,193

5,30...3,32

90,03,305,96

5,60...4,62

30,318

4,1841903,195

81,219,1205,93

30...1,29

19,129

3,90...3,921,91

05,918

3,1853,2001,184

34,601054

7,569

3

2

1

22

22

222

22

222

222

2

E

Tot

RG

RS

E

GEN

E

KON

REP

SSCFSS

SS

CFSS

CFSS

CFSS

CFSS

CFSS

CFSS

CF

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ANOVA

SR df SS MS Fhit Ftab

Rep.

Kon.

E1

Gen.

E2

K*G

E3

2

5

10

2

4

10

20

9,05

12,19

2,81

3,30

0,90

4,45

3,44

4,52

2,44

0,28

1,15

0,23

0,44

0,17

8,71*

5ns

2,85ns

6,43

9,6

4,37

Total 52 36,17

PROC GLM; CLASS BLOCKS TREATS CROSS; MODEL WHATEVER = BLOCKS TREATS BLOCKS*TREATS CROSS CROSS*BLOCKS CROSS*TREATS; TEST H=BLOCKS TREATS E=BLOCKS*TREATS; TEST H=CROSS E=CROSS*BLOCKS;RUN;

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RCB REPEATED IN TIME

Field marks: Multiple measurements of the

same experimental subjects are made in time.

Treatments are assigned at random within blocks of adjacent subjects, each treatment once per block.

The number of blocks is the number of replications.

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this example.

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LAYOUT

First Block I A B C D E F Block II F A E B D C Block III C B F A D ESecond Block I A B C D E F Block II F A E B D C Block III C B F A D EThird Block I A B C D E F Block II F A E B D C Block III C B F A D E

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ANOVA RCBD REPEATED TIMESource of

variationDegrees of

freedoma

Sums ofsquares (SSQ)

Meansquare (MS)

F

Blocks (B) b-1 SSQB SSQB/(b-1) MSB/MSEm

Treatment (Tr) t-1 SSQTr1 SSQTr/(t-1) MSTr/MSEm

Error-main (Em) (b-1)*(t-1) SSQEm SSQEm/((b-1)*(t-1))  

Time (Ti) (s-1) SSQTi SSQTi/(s-1) MSTi/MSE

Time X Blocks (TxB) (s-1)*(b-1) SSQTxB SSQTxB/((s-1)*(b-1)) MSTxB/MSE

Time X Treatments (TxT) (s-1)*(t-1) SSQTxT SSQTxT/((s-1)*(t-1)) MSTxT/MSE

Error (E) (s-1)*(t-1)*(b-1) SSQE SSQE/((s-1)*(t-1)*(b-1))  

Total (Tot) f*s*b-1 SSQTot    

awhere t=number of treatments, s=number of times measurements are taken, and b=number of blocks or replications.

04/22/23 11Erlina Ambarwati

SAMPLE SAS GLM STATEMENTS:

PROC GLM; CLASS BLOCKS TREAT; MODEL TIME1 TIME2 TIME3 =

BLOCKS TREAT; REPEATED TIME /PRINTE;RUN;

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RCB REPEATED AT MORE THAN ONE LOCATIONField marks: Blocks are laid out at more than one location.

Treatments are assigned at random to those blocks as below.

Treatments are assigned at random within blocks of adjacent subjects, each treatment once per block.

The number of blocks is the number of replications.

Any treatment can be adjacent to any other treatment, but not to the same treatment within the block.

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LAY OUT MULTILOCATIONS

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ANOVA MULTILOCATIONSSource of

variationDegrees of

freedoma

Sums ofsquares (SSQ)

Meansquare (MS)

F

Locations (L) l-1 SSQL SSQL/(l-1) MSL/MSEl

Error for Locations (El) l*(b-1) SSQEl SSQEl/(l*(b-1))  

Treatments (Tr) t-1 SSQTr SSQTr/(t-1) MSTr/MSE

Treatments X Locations (TxL) (t-1)*(l-1) SSQTxL SSQTxL/((t-1)*(l-1)) MSTxL/MSE

Error (E) l*(t-1)*(b-1) SSQE SSQE/(l*(t-1)*(b-1))  

Total (Tot) l*t*b-1 SSQTot    

awhere l=number of locations, t=number of treatments and b=number of blocks or replications.

04/22/23 15Erlina Ambarwati

SAMPLE SAS GLM STATEMENTS:

PROC GLM; CLASS LOCS BLOCKS TREATS; MODEL WHATEVER = LOCS

LOCS(BLOCKS) TREATS TREATS*LOCS ;

TEST H = LOCS E = LOCS(BLOCKS);RUN; 

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