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15 Examples 252ltage example 5−3−6 from the GENSTAT REML manual Residuals vs Fitted valuResiduals (Y) −1.08: 1.45 Fitted values (X) 15.56: 16.81Figure 15.2 Residual plot for the voltage dataof the variance parameters. These Comp/SE statistics cannot be used to test thenull hypothesis that the variance component is zero. If we had used this crudemeasure then the conclusions would have been inconsistent with the conclusionsobtained from the REML log-likelihood ratio (see Table 15.3).Source Model terms Gamma Component Comp/SE % Csetstat 10 10 0.233417 0.119370E-01 1.35 0 Psetstat.regulatr 80 64 0.601817 0.307771E-01 3.64 0 Pteststat 4 4 0.642752E-01 0.328705E-02 0.98 0 PVariance 256 255 1.00000 0.511402E-01 9.72 0 PTable 15.3: REML log-likelihood ratio for the variance components in the voltagedataREML −2×terms log-likelihood difference P-value− setstat 200.31 5.864 .0077− setstat.regulatr 184.15 38.19 .0000− teststat 199.71 7.064 .0039
15 Examples 25315.5 Balanced repeated measures - HeightThe data for this example is taken from the GENSTAT manual. It consists ofa total of 5 measurements of height (cm) taken on 14 plants. The 14 plantswere either diseased or healthy and were arranged in a glasshouse in a completelyrandom design. The heights were measured 1, 3, 5, 7 and 10 weeks after theplants were placed in the glasshouse. There were 7 plants in each treatment. Thedata are depicted in Figure 15.3 obtained by qualifier line!Y y1 !G tmt !JOINin the following multivariate ASReml job.This is plant data multivariateY=y1 X=Traits G=tmtY−axis: 21.0000 130.5000 X−axis: 0.5000 5.50001 2Figure 15.3 Trellis plot of the height for each of 14 plantsIn the following we illustrate how various repeated measures analyses can beconducted in ASReml. For these analyses it is convenient to arrange the datain a multivariate form, with 7 fields representing the plant number, treatmentidentification and the 5 heights. The ASReml input file, up to the specificationof the R structure isThis is plant data multivariatetmt !A # Diseased Healthyplant 14y1 y3 y5 y7 y10grass.asd !skip 1 !ASUV
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ASRemlUser GuideRelease 2.0A R Gilm
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Published by:E-mail:Website:VSN Int
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PrefaceiiASReml is one of several u
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ContentsPrefaceiList of TablesxviiL
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Contentsvi3.3 The ASReml data file
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ContentsviiiCombining rows from sep
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Contentsx7.6 Variance structure qua
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Contentsxii12.2 The command line .
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Contentsxiv15 Examples 24115.1 Intr
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List of Tablesxvi7.3 Details of the
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List of Figuresxix15.8 Rice bloodwo
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1 Introduction 21.1 What ASReml can
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1 Introduction 41.4 How to use this
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2 Some theoryThe linear mixed model
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2 Some theory 8laid out in a rectan
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2 Some theory 10product of matrices
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2 Some theory 12where H = R + ZGZ
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2 Some theory 14where y i is the
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2 Some theory 162.4 Combining varia
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2 Some theory 18balanced one-way cl
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2 Some theory 20L, r × p, and l, r
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2 Some theory 22the terms A, B, C,
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2 Some theory 24Kenward and Roger A
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3 A guided tourIntroductionNebraska
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3 A guided tour 28column rectangula
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3 A guided tour 30(see Chapter 2) t
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3 A guided tour 32els. Similarly fo
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3 A guided tour 34mand to run nin89
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3 A guided tour 36* SYNTAX change:
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3 A guided tour 38repl 3 -0.8713 1.
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3 A guided tour 40title linenin all
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4 Data file preparation 424.1 Intro
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4 Data file preparation 44Fixed for
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5 Command file: Reading the data 46
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6 Command file: Specifying theterms
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6 Command file: Specifying the term
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7 Command file: Specifying variance
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8 Command file: Multivariate analys
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9 Command file: Genetic analysisInt
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9 Command file: Genetic analysis 15
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10 Tabulation of the data andpredic
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10 Tabulation of the data and predi
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11 Functions of variancecomponentsI
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11 Functions of variance components
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11 Functions of variance components
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12 Command file: Running the jobInt
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12 Command file: Running the job 17
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13 Description of output filesIntro
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13 Description of output files 190A
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13 Description of output files 192i
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13 Description of output files 194f
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13 Description of output files 196.
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13 Description of output files 198o
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13 Description of output files 200E
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Page 228 and 229: NIN alliance trial 1989 9a 1Residua
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Page 234 and 235: 14 Error messagesIntroductionCommon
Page 236 and 237: 14 Error messages 214filename!last
Page 238 and 239: 14 Error messages 216variety !AQUAL
Page 240 and 241: 14 Error messages 2188. misspelt va
Page 242 and 243: 14 Error messages 220Missing/faulty
Page 244 and 245: 14 Error messages 222Last line read
Page 246 and 247: 14 Error messages 224Model specific
Page 248 and 249: 14 Error messages 226:11 column 11
Page 250 and 251: 14 Error messages 22814.5 Informati
Page 252 and 253: 14 Error messages 230List of warnin
Page 254 and 255: 14 Error messages 232Alphabetical l
Page 264 and 265: 15 Examples 24215.1 IntroductionIn
Page 266 and 267: 15 Examples 244For simple variance
Page 268 and 269: 15 Examples 2460.2_cwt Marvellous 1
Page 270 and 271: 15 Examples 248The input file conta
Page 272 and 273: 15 Examples 250Source Model terms G
Page 276 and 277: 15 Examples 254The focus is modelli
Page 278 and 279: 15 Examples 256y1 y3 y5 y7 y10 ~ Tr
Page 280 and 281: 15 Examples 258power model shown in
Page 282 and 283: 15 Examples 260Residual US=UnStr 2
Page 284 and 285: 15 Examples 262the current model).
Page 286 and 287: 15 Examples 264Slate Hall example f
Page 288 and 289: 15 Examples 266Predicted values of
Page 290 and 291: 15 Examples 268wheat.asd !skip 1 !D
Page 292 and 293: Tullibigeal trial i2 1Variogram of
Page 294 and 295: 15 Examples 272column evaluated at
Page 296 and 297: 15 Examples 274this is for the pair
Page 298 and 299: 15 Examples 276Table 15.8: Estimate
Page 300 and 301: 15 Examples 278(and in fact necessa
Page 302 and 303: 15 Examples 280Tr.run 22 0 US .79 .
Page 304 and 305: 15 Examples 282Interpretation of re
Page 306 and 307: 15 Examples 284The independence of
Page 308 and 309: 15 Examples 286Note that the data f
Page 310 and 311: 15 Examples 288Table 15.11 Orange d
Page 312 and 313: 15 Examples 290217Predicted values
Page 314 and 315: 15 Examples 292105Residual0-5-10200
Page 316 and 317: 15 Examples 294Table 15.13: REML es
Page 318 and 319: 15 Examples 29615*0. #Asreml will e
Page 320 and 321: 15 Examples 298Covariance/Variance/
Page 322 and 323: 15 Examples 300Eigen values 4.382 0
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15 Examples 302Animal modelIn this
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15 Examples 304additive genetic var
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BibliographyAbramowitz, M. and Steg
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Bibliography 308Gilmour, A. R., Cul
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Bibliography 310Schall, R. (1991).
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IndexABORTASR.NOW, 65FINALASR.NOW,
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Index 314free format, 42functions o
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Index 316!==, 53!>, 53!>=, 53!*, 53
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Index 318!STEP, 71!SUBSET, 71!SUB,
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Index 320parameter, 7variance compo
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