Introduction | Use asreml to analyse the logits | References

Introduction | Use lmerTest and lm to analyse the logits | References

1. Set up the initial model for this experiment | 2. Compare a series of information criteria to select a linear mixed model for the data | 3. Diagnostic checking using residual plots and variofaces | 4. Prediction production and presentation | References

growthPheno-package | anom | args4chosen_plot | args4chosen_smooth | args4devnboxes_plot | args4meddevn_plot | args4profile_plot | args4smoothing | as.smooths.frame | byIndv4Intvl_GRsAvg | byIndv4Intvl_GRsDiff | byIndv4Intvl_ValueCalc | byIndv4Intvl_WaterUse | byIndv4Times_GRsDiff | byIndv4Times_periodicRates | byIndv4Times_SplinesGRs | byIndv4Times_WaterUse | byIndv_ValueCalc | calcLagged | calcTimes | cumulate | designFactors | exampleData | getTimesSubset | growthPheno-deprecated | GrowthRates | importExcel | intervalPVA.data.frame | is.smooths.frame | plotAnom | plotCorrmatrix | plotDeviationsBoxes | plotImagetimes | plotProfiles | plotSmoothsComparison | plotSmoothsDevnBoxplots | plotSmoothsMedianDevns | prepImageData | probeSmooths | PVA | PVA.data.frame | PVA.matrix | rcontrib | rcontrib.data.frame | rcontrib.matrix | RicePrepped.dat | RiceRaw.dat | smooths.frame | smoothSpline | tomato.dat | traitExtractFeatures | traitSmooth | twoLevelOpcreate | validSmoothsFrame | WUI | Index

Initialize | Step 1: Import, select and derive longitudinal data | Step 2: Exploratory analysis | Step 3: Choose the smoothing method and DF | Step 4: Identify potential outlers and clean the data | Step 5: Extract per-cart traits | Form continuous and interval SIITs | Save image | References

Initialize | Step I: Import the longitudinal data | Step II: Investigate the smoothing of the PSA and obtain growth rates | Step III: Investigate the smoothing of the WU | Step IV: Identify potential outliers and remove if justified | Step V: Extract single-valued traits for each individual | Step VI: Save to files | Reference

1. Set up the maximal model for this experiment | 2. Perform a series of hypothesis tests to select a linear mixed model for the data | 3. Diagnostic checking using residual plots and variofaces | 4. Prediction production and presentation | References

1. Set up the maximal model for this experiment | 2. Obtaining information criteria for separate models | 3. Obtaining information criteria for a prescribed sequence of model changes | 4. Using information criteria to decide model changes | References

imageData-package | anom | anomPlot | calcLagged | calcTimes | corrPlot | cumulate | designFactors | exampleData | fitSpline | getDates | GrowthRates | imagetimesPlot | importExcel | intervalGRaverage | intervalGRdiff | intervalPVA | intervalValueCalculate | intervalWUI | longiPlot | longitudinalPrime | probeDF | PVA | rcontrib | RiceRaw.dat | splitContGRdiff | splitSplines | splitValueCalculate | twoLevelOpcreate | WUI | Index

Introduction | Single-allocation orthogonal design in R | Single-allocation, nonorthogonal design in R | Miscellaneous experimental design topics in R | Multiphase experiments in R

dae-package | ABC.Interact.dat | as.data.frame.pstructure | as.numfac | BIBDWheat.dat | blockboundaryPlot | Cabinet1.des | Casuarina.dat | correct.degfree | dae-deprecated | daeTips | decomp.relate | degfree | designAmeasures | designAnatomy | designBlocksGGPlot | designGGPlot | designLatinSqrSys | designPlot | designPlotlabels | designRandomize | designTwophaseAnatomies | detect.diff | efficiencies | efficiency.criteria | elements | Exp249.munit.des | extab | fac.ar1mat | fac.combine | fac.divide | fac.gen | fac.genfactors | fac.match | fac.meanop | fac.multinested | fac.nested | fac.recast | fac.recode | fac.split | fac.sumop | fac.uncombine | fac.uselogical | fac.vcmat | Fac4Proc.dat | fitted.aovlist | fitted.errors | get.daeRNGkind | get.daeTolerance | harmonic.mean | interaction.ABC.plot | is.allzero | is.projector | LatticeSquare_t49.des | makeLevsPadNums | marginality | mat.ar1 | mat.ar2 | mat.ar3 | mat.arma | mat.banded | mat.cor | mat.corg | mat.dirprod | mat.dirsum | mat.exp | mat.gau | mat.ginv | mat.I | mat.J | mat.ma1 | mat.ma2 | mat.ncssvar | mat.random | mat.sar | mat.sar2 | mat.Vpred | mat.Vpredicts | McIntyreTMV.dat | meanop | mpone | no.reps | Oats.dat | p2canon.object | pcanon.object | porthogonalize.list | power.exp | print.aliasing | print.projector | print.pstructure | print.summary.p2canon | print.summary.pcanon | proj2.combine | proj2.efficiency | proj2.eigen | projector | projector-class | projs.2canon | projs.combine.p2canon | pstructure.formula | pstructure.object | qqyeffects | rep.data.frame | resid.errors | residuals.aovlist | rmvnorm | Sensory3Phase.dat | set.daeRNGkind | set.daeTolerance | show-methods | SPLGrass.dat | strength | summary.p2canon | summary.pcanon | tukey.1df | yates.effects | Zncsspline | Index

asremlPlus-package | addBacktransforms.alldiffs | addPairwiseLetters.alldiffs | addSpatialModel.asrtests | addSpatialModelOnIC.asrtests | addto.test.summary | allDifferences.data.frame | alldiffs.object | angular | angular.mod | as.alldiffs | as.asrtests | as.predictions.frame | asremlPlus-deprecated | asremlPlusTips | asrtests.object | bootREMLRT.asreml | changeModelOnIC.asrtests | changeTerms.asrtests | ChickpeaEnd.dat | chooseModel | chooseModel.asrtests | chooseModel.data.frame | chooseSpatialModelOnIC.asrtests | convAsremlobj.asreml | convEffectNames2DataFrame.asreml | estimateV.asreml | exploreLSDs.alldiffs | facCombine.alldiffs | facRecast.alldiffs | facRename.alldiffs | findLSDminerrors.alldiffs | getASRemlVersionLoaded | getFormulae.asreml | getTestEntry.asrtests | getTestPvalue.asrtests | infoCriteria | is.alldiffs | is.asrtests | is.predictions.frame | isCompoundSymmetric.matrix | iterate.asrtests | Ladybird.dat | linTransform.alldiffs | loadASRemlVersion | LSD.frame | makeTPPSplineMats.data.frame | newfit.asreml | num.recode | Oats.dat | pairdiffsTransform.alldiffs | permute.square | permute.to.zero.lowertri | pickLSDstatistics.alldiffs | plotLSDerrors.alldiffs | plotLSDerrors.data.frame | plotLSDs.alldiffs | plotLSDs.data.frame | plotPredictions.data.frame | plotPvalues.alldiffs | plotPvalues.data.frame | plotVariofaces.data.frame | powerTransform | predictions.frame | predictPlus.asreml | predictPresent.asreml | print.alldiffs | print.asrtests | print.LSDdata | print.predictions.frame | print.test.summary | print.wald.tab | printFormulae.asreml | R2adj.asreml | ratioTransform.alldiffs | recalcLSD.alldiffs | recalcWaldTab.asrtests | redoErrorIntervals.alldiffs | REMLRT.asreml | renewClassify.alldiffs | reparamSigDevn.asrtests | rmboundary.asrtests | setvarianceterms.call | simulate.asreml | sort.alldiffs | sort.predictions.frame | subset.alldiffs | subset.list | testranfix.asrtests | testresidual.asrtests | testswapran.asrtests | validAlldiffs | validAsrtests | validPredictionsFrame | variofaces.asreml | WaterRunoff.dat | Wheat.dat | Index