output

/* Open the dataset and display the variables */

GET file 'C:\ \Plankton.sav'.

LIST id light strain t1 t2 t3 t4 t5 t6 t7 t8 t9 t10 t11 t12 t13 t14 t15 t16 t17 t18 t19.

List

Output Created

Comments

Data

Filter

Weight

Split File

N of Rows in Working Data File

Syntax

Processor Time

Elapsed Time

Input

Resources

00 00:00:00.010

00 00:00:00.000

LIST id light strain t1 t2 t3 t4 t5 t6 t7 t8 t9 t10 t11 t12 t13 t14 t15 t16 t17 t18 t19.

4

<none>

<none>

<none>

C:\ Plankton.sav

14-Jan-2011 04:48:07

Notes

C:\ Plankton.sav

The variables are listed in the following order:

LINE 1: ID Light Strain t1 t2 t3 t4 t5 t6

LINE 2: t7 t8 t9 t10 t11 t12 t13 t14 t15

LINE 3: t16 t17 t18 t19

ID: 1 1 1 2844 1924

2000 1934 1664 2344

t7: 1978 2958 3386 3060 4650

5448 6856 7476 5536

t16: 6264 13018 17092 13056

ID: 2 1 2 1554 1274

950 912 1066 2544

t7: 1350 1780 2648 3650 7054

5624 7934 11166 7350

t16: 10068 15498 25136 28700

ID: 3 2 1 2128 1962

1560 1688 1478 1744

t7: 2404 1394 2780 2478 4646

3882 4486 4558 4880

t16: 4314 7302 9880 11212

ID: 4 2 2 1406 1196

840 1422 588 1102

t7: 1092 1836 2778 2664 4570

4998 6430 6374 3564

t16: 7062 9874 21604 21444

Number of cases read: 4 Number of cases listed: 4

/* Demonstrate that modelling these data with 19 factors for time is incorrect */

/* I included this to show that 1) this model is incorrect, and 2) to verify the results you posted earlier */

TITLE "MODEL 0 - Incorrect GLM Model".

MODEL 0 - Incorrect GLM Model

GLM t1 t2 t3 t4 t5 t6 t7 t8 t9 t10 t11 t12 t13 t14 t15 t16 t17 t18 t19 by strain

/WSFACTOR = t 19

/WSDESIGN=t

/DESIGN=strain

/EMMEANS=tables( t*strain)

/PLOT=PROFILE( t*strain).

General Linear Model

Output Created

Comments

Data

Filter

Weight

Split File


Definition of Missing

Cases Used

Syntax

Processor Time

Elapsed Time

Input

Missing Value Handling

Resources

00 00:00:01.076

00 00:00:01.529

GLM t1 t2 t3 t4 t5 t6 t7 t8 t9 t10 t11 t12 t13 t14 t15 t16 t17 t18 t19 by strain /WSFACTOR = t 19 /WSDESIGN=t /DESIGN=strain /EMMEANS=tables( t*strain) /PLOT=PROFILE( t*strain).

Statistics are based on all cases with valid data for all variables in the model.

User-defined missing values are treated as missing.

4

<none>

<none>

<none>

C:\ Plankton.sav

14-Jan-2011 04:48:07

Notes

C:\ Plankton.sav


Dependent Variable

1

2

3

4

5

6

7

8

9

10

11

12

13

14

15

16

17

18

19 t19

t18

t17

t16

t15

t14

t13

t12

t11

t10

t9

t8

t7

t6

t5

t4

t3

t2

t1

tt

Within-Subjects Factors

Measure:MEASURE_1

N

1

2

Strain

2

2

Between-Subjects Factors


Sig.Error dfHypothesis dfFValue

Pillai's Trace

Wilks' Lambda

Hotelling's Trace

Roy's Largest Root

Pillai's Trace

Wilks' Lambda

Hotelling's Trace

Roy's Largest Root

t

t * Strain

.....a

.....a

.....a

.....a

.....a

.....a

.....a

.....a

EffectEffect

Multivariate Testsb

a. Cannot produce multivariate test statistics because of insufficient residual degrees of freedom.b. Design: Intercept + Strain Within Subjects Design: t

Sig.dfApprox. Chi-

SquareMauchly's W

t .170..000

Within Subjects EffectWithin Subjects Effect

Mauchly's Test of Sphericityb

Measure:MEASURE_1

Lower-boundHuynh-FeldtGreenhouse-

Geisser

Epsilona

t .056.431.083

Within Subjects EffectWithin Subjects Effect

Mauchly's Test of Sphericityb

Measure:MEASURE_1

Tests the null hypothesis that the error covariance matrix of the orthonormalized transformed dependent variables is proportional to an identity matrix.

a. May be used to adjust the degrees of freedom for the averaged tests of significance. Corrected tests are displayed in the Tests of Within-Subjects Effects table.b. Design: Intercept + Strain Within Subjects Design: t


Sig.FMean SquaredfType III Sum of Squares

Sphericity Assumed

Greenhouse-Geisser

Huynh-Feldt

Lower-bound

Sphericity Assumed

Greenhouse-Geisser

Huynh-Feldt

Lower-bound

Sphericity Assumed

Greenhouse-Geisser

Huynh-Feldt

Lower-bound

t

t * Strain

Error(t)

39895197.5792.00079790395.158

5137742.47215.53079790395.158

26774976.1762.98079790395.158

2216399.8653679790395.158

.1286.3422.530E81.0002.530E8

.0016.34232584220.4907.7652.530E8

.0866.3421.698E81.4902.530E8

.0006.34214056691.690182.530E8

.01951.4282.052E91.0002.052E9

.00051.4282.642E87.7652.052E9

.00551.4281.377E91.4902.052E9

.00051.4281.140E8182.052E9

SourceSource

Tests of Within-Subjects Effects

Measure:MEASURE_1



Linear

Quadratic

Cubic

Order 4

Order 5

Order 6

Order 7

Order 8

Order 9

Order 10

Order 11

Order 12

Order 13

Order 14

Order 15

Order 16

Order 17

Order 18

Linear

t

t * Strain .1336.0541.430E811.430E8

.0919.4792496654.75412496654.754

.2632.384198300.8601198300.860

.0998.6473811071.82313811071.823

.1355.9411608616.26311608616.263

.002629.0462080011.61512080011.615

.773.10864424.299164424.299

.543.5271050944.20611050944.206

.4001.127775182.5251775182.525

.971.002577.3161577.316

.1127.4264821716.87014821716.870

.03328.80431351202.696131351202.696

.03924.05947510261.662147510261.662

.1276.39912470087.156112470087.156

.2892.0442824035.04912824035.049

.01185.83036275392.587136275392.587

.001887.97954558977.045154558977.045

.010101.7074.129E814.129E8

.01660.8371.437E911.437E9

Source tSource t

Tests of Within-Subjects Contrasts

Measure:MEASURE_1



Quadratic

Cubic

Order 4

Order 5

Order 6

Order 7

Order 8

Order 9

Order 10

Order 11

Order 12

Order 13

Order 14

Order 15

Order 16

Order 17

Order 18

t * Strain

.882.0287379.30017379.300

.469.78765488.453165488.453

.2282.9541301775.32511301775.325

.1256.5621776640.46811776640.468

.001802.4932653533.35212653533.352

.3081.8331089207.89011089207.890

.735.151300952.5521300952.552

.493.693476410.4701476410.470

.1913.8001330804.85111330804.851

.3411.534995943.9701995943.970

.2882.0512232656.34412232656.344

.438.9241824926.74811824926.748

.996.00066.570166.570

.2093.3514630572.19514630572.195

.03527.08911448761.843111448761.843

.003368.52122642559.438122642559.438

.06414.10357247340.784157247340.784

Source tSource t


Measure:MEASURE_1


Mean SquaredfType III Sum of Squares

Linear

Quadratic

Cubic

Order 4

Order 5

Order 6

Order 7

Order 8

Order 9

Order 10

Order 11

Order 12

Order 13

Order 14

Order 15

Order 16

Order 17

Order 18

Error(t)

263375.8552526751.711

83183.6212166367.242

440751.3122881502.624

270748.9232541497.847

3306.61326613.226

594215.45721188430.915

1995267.83123990535.662

687836.37821375672.757

350217.0972700434.194

649300.06021298600.120

1088446.87122176893.741

1974763.99023949527.980

1948734.56823897469.136

1381851.92822763703.855

422640.1762845280.352

61441.7232122883.446

4059337.75628118675.512

23619777.419247239554.839

Source tSource t


Measure:MEASURE_1


Intercept

Strain

Error 27349083.421254698166.842

.3261.66645551450.579145551450.579

.01283.0052.270E912.270E9

SourceSource

Tests of Between-Subjects Effects

Measure:MEASURE_1Transformed Variable:Average

Estimated Marginal Means


Std. ErrorMean Upper BoundLower Bound

95% Confidence Interval

1

2

1

2

1

2

1

2

1

2

1

2

1

2

1

2

1

2

1

2

1

2

1

2

1

2

1

2

1

2

1

2

1

2

3

4

5

6

7

8

9

10

11

12

13

14

15

16

14015.6603114.3401266.8148565.000

10739.660-161.6601266.8145289.000

11302.145-388.1451358.4985457.000

11053.145-637.1451358.4985208.000

17304.828235.1721983.6208770.000

14551.828-2517.8281983.6206017.000

11451.9672912.033992.4037182.000

9940.9671401.033992.4035671.000

7876.5112745.489596.2635311.000

7230.5112099.489596.2634665.000

9590.7092033.291878.2285812.000

8426.709869.291878.2284648.000

4898.7241415.276404.8023157.000

4510.7241027.276404.8022769.000

3655.8311770.169219.1282713.000

4025.8312140.169219.1283083.000

4188.709-572.709553.3121808.000

4556.709-204.709553.3122176.000

1978.621463.379176.0821221.000

2948.6211433.379176.0822191.000

4198.908-552.908552.1961823.000

4419.908-331.908552.1962044.000

1607.25346.747181.342827.000

2351.253790.747181.3421571.000

2028.358305.642200.1921167.000

2672.358949.642200.1921811.000

1584.935205.065160.351895.000

2469.9351090.065160.3511780.000

1366.9871103.01330.6761235.000

2074.9871811.01330.6761943.000

2592.217367.783258.4961480.000

3598.2171373.783258.4962486.000

t Straint Strain

t * Strain

Measure:MEASURE_1


Std. ErrorMean Upper BoundLower Bound

95% Confidence Interval

1

2

1

2

1

2

17

18

19

36460.81713683.1832646.92925072.000

23522.817745.1832646.92912134.000

35586.04611153.9542839.18923370.000

25702.0461269.9542839.18913486.000

24884.422487.5782835.09312686.000

22358.422-2038.4222835.09310160.000

t Straint Strain

t * Strain

Measure:MEASURE_1

Profile Plots

t

19181716151413121110987654321

Est

imat

ed M

arg

inal

Mea

ns

30000

25000

20000

15000

10000

5000

0

Estimated Marginal Means of MEASURE_1

21

Strain


/* Convert dataset from wide-format to long-format */

varstocases

/make growth from t1 t2 t3 t4 t5 t6 t7 t8 t9 t10 t11 t12 t13 t14 t15 t16 t17 t18 t19

/index=time.

Variables to Cases

Output Created

Comments

Data

Filter

Weight

Split File

Syntax

Processor Time

Elapsed Time

Input

Resources

00 00:00:00.000

00 00:00:00.000

varstocases /make growth from t1 t2 t3 t4 t5 t6 t7 t8 t9 t10 t11 t12 t13 t14 t15 t16 t17 t18 t19 /index=time.

<none>

<none>

<none>

C: Plankton.sav

14-Jan-2011 04:48:08

Notes

C:\ Plankton.sav

LabelName

<none>growth

<none>time

Generated Variables

Variables In

Variables Out 5

22

Processing Statistics

list cases /var=id light strain time growth.

List


Output Created

Comments

Filter

Weight

Split File


Syntax

Processor Time

Elapsed Time

Input

Resources

00 00:00:00.000

00 00:00:00.000

list cases /var=id light strain time growth.

76

<none>

<none>

<none>

14-Jan-2011 04:48:08

Notes

C:\ Plankton.sav

ID Light Strain time growth

1 1 1 1 2844

1 1 1 2 1924

1 1 1 3 2000

1 1 1 4 1934

1 1 1 5 1664

1 1 1 6 2344

1 1 1 7 1978

1 1 1 8 2958

1 1 1 9 3386

1 1 1 10 3060

1 1 1 11 4650

1 1 1 12 5448

1 1 1 13 6856

1 1 1 14 7476

1 1 1 15 5536

1 1 1 16 6264

1 1 1 17 13018

1 1 1 18 17092

1 1 1 19 13056

2 1 2 1 1554

2 1 2 2 1274

2 1 2 3 950


2 1 2 4 912

2 1 2 5 1066

2 1 2 6 2544

2 1 2 7 1350

2 1 2 8 1780

2 1 2 9 2648

2 1 2 10 3650

2 1 2 11 7054

2 1 2 12 5624

2 1 2 13 7934

2 1 2 14 11166

2 1 2 15 7350

2 1 2 16 10068

2 1 2 17 15498

2 1 2 18 25136

2 1 2 19 28700

3 2 1 1 2128

3 2 1 2 1962

3 2 1 3 1560

3 2 1 4 1688

3 2 1 5 1478

3 2 1 6 1744

3 2 1 7 2404

3 2 1 8 1394

3 2 1 9 2780

3 2 1 10 2478

3 2 1 11 4646

3 2 1 12 3882

3 2 1 13 4486

3 2 1 14 4558

3 2 1 15 4880

3 2 1 16 4314

3 2 1 17 7302

3 2 1 18 9880

3 2 1 19 11212

4 2 2 1 1406

4 2 2 2 1196

4 2 2 3 840

4 2 2 4 1422

4 2 2 5 588


4 2 2 6 1102

4 2 2 7 1092

4 2 2 8 1836

4 2 2 9 2778

4 2 2 10 2664

4 2 2 11 4570

4 2 2 12 4998

4 2 2 13 6430

4 2 2 14 6374

4 2 2 15 3564

4 2 2 16 7062

4 2 2 17 9874

4 2 2 18 21604

4 2 2 19 21444

Number of cases read: 76 Number of cases listed: 76

/* Graph empirical growth plots */

FORMATS time growth (f3.0) id (f2.0).

GGRAPH

/GRAPHDATASET NAME="GraphDataset" VARIABLES= growth time id

/GRAPHSPEC SOURCE=INLINE INLINETEMPLATE=[ "<setWrapPanels/>"].

BEGIN GPL

SOURCE: s=userSource( id( "GraphDataset" ) )

DATA: growth=col( source(s), name( "growth" ) )

DATA: time=col( source(s), name( "time" ) )

DATA: id=col( source(s), name( "id" ), unit.category() )

GUIDE: text.title( label( "Empirical Growth Plots" ) )

GUIDE: axis( dim( 1 ), label( "Time" ) )

GUIDE: axis( dim( 2 ), label( "Growth" ) )

GUIDE: axis( dim( 3 ), label( "ID" ), opposite() )

SCALE: linear( dim( 1 ), min( 0 ), max( 20 ) )


ELEMENT: line( position( smooth.spline( summary.mode( time * growth * id ) ) ))

ELEMENT: point( position( summary.mode( time * growth * id ) ) )

END GPL.

GGraph


Output Created

Comments

Filter

Weight

Split File


Syntax

Processor Time

Elapsed Time

Input

Resources

00 00:00:00.475

00 00:00:00.530

GGRAPH /GRAPHDATASET NAME="GraphDataset" VARIABLES= growth time id /GRAPHSPEC SOURCE=INLINE INLINETEMPLATE=[ "<setWrapPanels/>"].BEGIN GPLSOURCE: s=userSource( id( "GraphDataset" ) )DATA: growth=col( source(s), name( "growth" ) )DATA: time=col( source(s), name( "time" ) )DATA: id=col( source(s), name( "id" ), unit.category() )GUIDE: text.title( label( "Empirical Growth Plots" ) )GUIDE: axis( dim( 1 ), label( "Time" ) )GUIDE: axis( dim( 2 ), label( "Growth" ) )GUIDE: axis( dim( 3 ), label( "ID" ), opposite() )SCALE: linear( dim( 1 ), min( 0 ), max( 20 ) )SCALE: linear( dim( 2 ), min( 500 ), max( 25000 ) )ELEMENT: line( position( smooth.spline( summary.mode( time * growth * id ) ) ))ELEMENT: point( position( summary.mode( time * growth * id ) ) )END GPL.

76

<none>

<none>

<none>

14-Jan-2011 04:48:08

Notes

C:\ Plankton.sav


Gro

wth

25000

20000

15000

10000

5000

Time

20151050

Gro

wth

25000

20000

15000

10000

5000

Time

20151050

43

21

Empirical Growth Plots

/* Graph linear empirical growth plots */

GGRAPH


/GRAPHSPEC SOURCE=INLINE INLINETEMPLATE=[ "<setWrapPanels/>"].

BEGIN GPL





GUIDE: text.title( label( "Linear Empirical Growth Plots" ) )




GUIDE: axis( dim( 3 ), label( "ID" ), opposite() )



ELEMENT: line( position(smooth.linear( time * growth * id ) ))

ELEMENT: point( position( summary.mode( time * growth * id ) ) )

END GPL.

GGraph

Output Created

Comments

Filter

Weight

Split File


Syntax

Processor Time

Elapsed Time

Input

Resources

00 00:00:00.273

00 00:00:00.296

GGRAPH /GRAPHDATASET NAME="GraphDataset" VARIABLES= growth time id /GRAPHSPEC SOURCE=INLINE INLINETEMPLATE=[ "<setWrapPanels/>"].BEGIN GPLSOURCE: s=userSource( id( "GraphDataset" ) )DATA: growth=col( source(s), name( "growth" ) )DATA: time=col( source(s), name( "time" ) )DATA: id=col( source(s), name( "id" ), unit.category() )GUIDE: text.title( label( "Linear Empirical Growth Plots" ) )GUIDE: axis( dim( 1 ), label( "Time" ) )GUIDE: axis( dim( 2 ), label( "Growth" ) )GUIDE: axis( dim( 3 ), label( "ID" ), opposite() )SCALE: linear( dim( 1 ), min( 0 ), max( 20 ) )SCALE: linear( dim( 2 ), min( 500 ), max( 25000 ) )ELEMENT: line( position(smooth.linear( time * growth * id ) ))ELEMENT: point( position( summary.mode( time * growth * id ) ) )END GPL.

76

<none>

<none>

<none>

14-Jan-2011 04:48:09

Notes


C:\ Plankton.sav

Gro

wth

25000

20000

15000

10000

5000

Time

20151050

Gro

wth

25000

20000

15000

10000

5000

Time

20151050

43

21

Linear Empirical Growth Plots

/* Graph spaghetti empirical growth plots */

GGRAPH


/GRAPHSPEC SOURCE=INLINE .

BEGIN GPL






GUIDE: text.title( label( "Spaghetti Plot" ) )



GUIDE: legend( aesthetic( aesthetic.shape.interior ), null() )



SCALE: cat( aesthetic( aesthetic.shape.interior ) )

ELEMENT: line( position( smooth.spline( summary.mode( time * growth ) ) ), shape.interior( id ))

END GPL.

GGraph


Output Created

Comments

Filter

Weight

Split File


Syntax

Processor Time

Elapsed Time

Input

Resources

00 00:00:00.252

00 00:00:00.281

GGRAPH /GRAPHDATASET NAME="GraphDataset" VARIABLES= growth time id /GRAPHSPEC SOURCE=INLINE .BEGIN GPLSOURCE: s=userSource( id( "GraphDataset" ) )DATA: growth=col( source(s), name( "growth" ) )DATA: time=col( source(s), name( "time" ) )DATA: id=col( source(s), name( "id" ), unit.category() )GUIDE: text.title( label( "Spaghetti Plot" ) )GUIDE: axis( dim( 1 ), label( "Time" ) )GUIDE: axis( dim( 2 ), label( "Growth" ) )GUIDE: legend( aesthetic( aesthetic.shape.interior ), null() )SCALE: linear( dim( 1 ), min( 0 ), max( 20 ) )SCALE: linear( dim( 2 ), min( 500 ), max( 25000 ) )SCALE: cat( aesthetic( aesthetic.shape.interior ) )ELEMENT: line( position( smooth.spline( summary.mode( time * growth ) ) ), shape.interior( id ))END GPL.

76

<none>

<none>

<none>

14-Jan-2011 04:48:09

Notes

C:\ Plankton.sav


Time

20151050

Gro

wth

25000

20000

15000

10000

5000

Spaghetti Plot

/* Graph linear spaghetti empirical growth plots */

GGRAPH


/GRAPHSPEC SOURCE=INLINE .

BEGIN GPL





GUIDE: text.title( label( "Linear Spaghetti Plot" ) )







SCALE: cat( aesthetic( aesthetic.shape.interior ) )

ELEMENT: line( position( smooth.linear( summary.mode( time * growth ) ) ), shape.interior( id ))

ELEMENT: line( position( smooth.linear( time * growth ) ), color(color.red) )

END GPL.

GGraph


Output Created

Comments

Filter

Weight

Split File


Syntax

Processor Time

Elapsed Time

Input

Resources

00 00:00:00.261

00 00:00:00.312

GGRAPH /GRAPHDATASET NAME="GraphDataset" VARIABLES= growth time id /GRAPHSPEC SOURCE=INLINE .BEGIN GPLSOURCE: s=userSource( id( "GraphDataset" ) )DATA: growth=col( source(s), name( "growth" ) )DATA: time=col( source(s), name( "time" ) )DATA: id=col( source(s), name( "id" ), unit.category() )GUIDE: text.title( label( "Linear Spaghetti Plot" ) )GUIDE: axis( dim( 1 ), label( "Time" ) )GUIDE: axis( dim( 2 ), label( "Growth" ) )GUIDE: legend( aesthetic( aesthetic.shape.interior ), null() )SCALE: linear( dim( 1 ), min( 0 ), max( 20 ) )SCALE: linear( dim( 2 ), min( 500 ), max( 25000 ) )SCALE: cat( aesthetic( aesthetic.shape.interior ) )ELEMENT: line( position( smooth.linear( summary.mode( time * growth ) ) ), shape.interior( id ))ELEMENT: line( position( smooth.linear( time * growth ) ), color(color.red) )END GPL.

76

<none>

<none>

<none>

14-Jan-2011 04:48:09

Notes

C:\ Plankton.sav


Time

20151050

Gro

wth

25000

20000

15000

10000

5000

Linear Spaghetti Plot

/* Graph linear spaghetti empirical growth plots by strain */

VALUE LABELS strain 1 "CCAP" 2 "PCC".

GGRAPH

/GRAPHDATASET NAME="GraphDataset" VARIABLES= growth time id strain

/GRAPHSPEC SOURCE=INLINE INLINETEMPLATE=["<setWrapPanels/>"].

BEGIN GPL





DATA: strain=col( source(s), name( "strain" ), unit.category() )

GUIDE: text.title( label( "Linear Plot by Strain" ) )




GUIDE: axis( dim( 3 ), label( "Strain" ), opposite() )




ELEMENT: line( position( smooth.linear( summary.mode( time * growth * strain) ) ), shape.interior( id ))

ELEMENT: line( position( smooth.linear( time * growth * strain) ), color(color.red) )

END GPL.

GGraph


Output Created

Comments

Filter

Weight

Split File


Syntax

Processor Time

Elapsed Time

Input

Resources

00 00:00:00.272

00 00:00:00.546

GGRAPH /GRAPHDATASET NAME="GraphDataset" VARIABLES= growth time id strain /GRAPHSPEC SOURCE=INLINE INLINETEMPLATE=["<setWrapPanels/>"].BEGIN GPLSOURCE: s=userSource( id( "GraphDataset" ) )DATA: growth=col( source(s), name( "growth" ) )DATA: time=col( source(s), name( "time" ) )DATA: id=col( source(s), name( "id" ), unit.category() )DATA: strain=col( source(s), name( "strain" ), unit.category() )GUIDE: text.title( label( "Linear Plot by Strain" ) )GUIDE: axis( dim( 1 ), label( "Time" ) )GUIDE: axis( dim( 2 ), label( "Growth" ) )GUIDE: axis( dim( 3 ), label( "Strain" ), opposite() )GUIDE: legend( aesthetic( aesthetic.shape.interior ), null() )SCALE: linear( dim( 1 ), min( 0 ), max( 20 ) )SCALE: linear( dim( 2 ), min( 500 ), max( 25000 ) )ELEMENT: line( position( smooth.linear( summary.mode( time * growth * strain) ) ), shape.interior( id ))ELEMENT: line( position( smooth.linear( time * growth * strain) ), color(color.red) )END GPL.

76

<none>

<none>

<none>

14-Jan-2011 04:48:10

Notes

C:\ Plankton.sav


Time

20151050

Gro

wth

25000

20000

15000

10000

5000

Time

20151050

PCCCCAP

Linear Plot by Strain

/* Model growth over time to show time is significant -- unstructured covariance structure */

TITLE "Model 1 - Uncondtional Growth".

Model 1 - Uncondtional Growth

MIXED growth by time

/METHOD=ml

/FIXED= time

/REPEATED=time | subject(id) covtype(un).

Mixed Model Analysis

Output Created

Comments

Filter

Weight

Split File



Cases Used

Syntax

Processor Time

Elapsed Time

Input


Resources

00 00:00:00.008

00 00:00:00.000

MIXED growth by time /METHOD=ml /FIXED= time /REPEATED=time | subject(id) covtype(un).



76

<none>

<none>

<none>

14-Jan-2011 04:48:10

Notes

C:\ Plankton.sav

Model cannot be fitted because number of observations is less than or equal to number of model parameters.

Warnings

/* Model growth over time by strain and interaction -- compound symmetric covariance structure */

TITLE "Model 2 - Uncontrolled Effects of Strain".

Model 2 - Uncontrolled Effects of Strain

MIXED growth by strain time

/METHOD=ml

/FIXED=strain time strain*time

/REPEATED=time | subject(id) covtype(cs)

/SAVE=fixpred(pred).

Mixed Model Analysis

Output Created

Comments

Filter

Weight

Split File



Cases Used

Syntax

Processor Time

Elapsed Time

pred

Input


Resources

Variables Created Fixed Predicted Values

00 00:00:00.091

00 00:00:00.093

MIXED growth by strain time /METHOD=ml /FIXED=strain time strain*time /REPEATED=time | subject(id) covtype(cs) /SAVE=fixpred(pred).



76

<none>

<none>

<none>

14-Jan-2011 04:48:10

Notes

C:\ Plankton.sav


Number of Parameters

Covariance Structure

Number of Levels

Intercept

Strain

time

Strain * time

time

Total

Fixed Effects

Repeated Effects

4079

2Compound Symmetry

19

1838

1819

12

11

Model Dimensiona

Number of Subjects

Subject Variables

Intercept

Strain

time

Strain * time

time

Total

Fixed Effects

Repeated Effects 4ID

Model Dimensiona

a. Dependent Variable: growth.

-2 Log Likelihood

Akaike's Information Criterion (AIC)

Hurvich and Tsai's Criterion (AICC)

Bozdogan's Criterion (CAIC)

Schwarz's Bayesian Criterion (BIC)

1456.746

1496.746

1457.231

1363.517

1283.517

Information Criteriaa

The information criteria are displayed in smaller-is-better forms.


Fixed Effects


Sig.FDenominator

dfNumerator df

Intercept

Strain

time

Strain * time .00012.6847218

.000102.8557218

.1423.3314.0001

.000166.0104.0001

SourceSource

Type III Tests of Fixed Effectsa


Covariance Parameters

Std. ErrorEstimate

CS diagonal offset

CS covariance

Repeated Measures

509006.58116661386.40935

184699.988791108199.9327

ParameterParameter

Estimates of Covariance Parametersa


/* Graph predicted linear growth plots by strain */

GGRAPH

/GRAPHDATASET NAME="GraphDataset" VARIABLES=time MEAN(pred)[name="MEAN_pred"] strain

/GRAPHSPEC SOURCE=INLINE.

BEGIN GPL



DATA: MEAN_pred=col( source(s), name( "MEAN_pred" ) )

DATA: strain=col( source(s), name( "strain" ), unit.category())

GUIDE: text.title( label( "Prototypical Linear Growth Plots" ) )

GUIDE: axis(dim(1), label( "Time" ) )

GUIDE: axis(dim(2), label( "Mean Fixed Predicted Values" ) )

GUIDE: legend( aesthetic(aesthetic.color.interior), label( "Strain" ) )

SCALE: linear(dim(1), min( 0 ), max( 20 ) )

SCALE: linear(dim(2), min( 500 ), max( 25000 ) )

ELEMENT: line( position( smooth.linear( time * MEAN_pred ) ), shape(strain))

END GPL.

GGraph


Output Created

Comments

Filter

Weight

Split File


Syntax

Processor Time

Elapsed Time

Input

Resources

00 00:00:00.243

00 00:00:00.312

GGRAPH /GRAPHDATASET NAME="GraphDataset" VARIABLES=time MEAN(pred)[name="MEAN_pred"] strain /GRAPHSPEC SOURCE=INLINE.BEGIN GPLSOURCE: s=userSource( id( "GraphDataset" ) )DATA: time=col( source(s), name( "time" ) )DATA: MEAN_pred=col( source(s), name( "MEAN_pred" ) )DATA: strain=col( source(s), name( "strain" ), unit.category())GUIDE: text.title( label( "Prototypical Linear Growth Plots" ) )GUIDE: axis(dim(1), label( "Time" ) )GUIDE: axis(dim(2), label( "Mean Fixed Predicted Values" ) )GUIDE: legend( aesthetic(aesthetic.color.interior), label( "Strain" ) )SCALE: linear(dim(1), min( 0 ), max( 20 ) )SCALE: linear(dim(2), min( 500 ), max( 25000 ) )ELEMENT: line( position( smooth.linear( time * MEAN_pred ) ), shape(strain))END GPL.

76

<none>

<none>

<none>

14-Jan-2011 04:48:10

Notes

C:\ Plankton.sav


Time

20151050

Mea

n F

ixed

Pre

dic

ted

Val

ues

25,000.00

20,000.00

15,000.00

10,000.00

5,000.00

Prototypical Linear Growth Plots

PCCCCAP

output

Documents

t design

t page

strain sphericity

tables t

profile t

strain emmeans

strain wsfactor

strain plot