predictions.frame: Description of a predictions object

In asremlPlus: Augments 'ASReml-R' in Fitting Mixed Models and Packages Generally in Exploring Prediction Differences

Description of a predictions object

Description

A data.frame of S3-class predictions.frame that stores the predictions for a fitted model.

as.predictions.frame is function that converts a data.frame to an object of this class.

is.predictions.frame is the membership function for this class; it tests that an object has class predictions.frame.

validPredictionsFrame can be used to test the validity of a predictions.frame.

Value

A data.frame that begins with the variables classifying the predictions, in the same order as in the classify, followed by a column of predictions that is named either predicted.value or backtransformed.predictions; it also contains columns named standard.error and est.status. The number of rows should equal the number of unique combinations of the classifying variables. While such a data.frame can be constructed from the beginning, the pvals component of the value produced by predict.asreml is a suitable value to supply for this argument. Note that the names standard.error and est.status have been changed to std.error and status in the pvals component produced by asreml-R4; if the new names are in the data.frame supplied to predictions, they will be returned to the previous names.

The data.frame may also include columns for the lower and upper values of error intervals, either standard error, confidence or half-LSD intervals. The names of these columns will consist of three parts separated by full stops: 1) the first part will be lower or upper; 2) the second part will be one of Confidence, StandardError or halfLeastSignificant; 3) the third component will be limits.

IF accuracy.threshold is set to a numeric value at the time the prediction.frame is formed, it will also include a column logical values named LSDwarning.

When halfLeastSignificant limits have been included in a predictions.frame, its attributes will include those that are not NULL of LSDtype, LSDby, LSDstatistic, LSDaccuracy and LSDvalues. LSDvalues are the LSD values used to calculate the halfLeastSignificant error.intervals and are an expanded version of the values stored in the assignedLSD column of the LSD.frame.

See predictPlus.asreml for more information.

Author(s)

Chris Brien

See Also

predictPlus.asreml, is.predictions.frame, as.predictions.frame, validPredictionsFrame

Examples

  data(Oats.dat)
  
  ## Use asreml to get predictions and associated statistics

  ## Not run: 
  m1.asr <- asreml(Yield ~ Nitrogen*Variety, 
                   random=~Blocks/Wplots,
                   data=Oats.dat)
  current.asrt <- as.asrtests(m1.asr)
  Var.pred <- asreml::predict.asreml(m1.asr, classify="Nitrogen:Variety", 
                                      sed=TRUE)
  if (getASRemlVersionLoaded(nchar = 1) == "3")
    Var.pred <- Var.pred$predictions
  Var.preds <- as.predictions.frame(Var.pred$pvals, se = "std.error", 
                                    est.status = "status")
  
## End(Not run)
  
  ## Use lmerTest and emmmeans to get predictions and associated statistics
  if (requireNamespace("lmerTest", quietly = TRUE) & 
      requireNamespace("emmeans", quietly = TRUE))
  {
    m1.lmer <- lmerTest::lmer(Yield ~ Nitrogen*Variety + (1|Blocks/Wplots),
                              data=Oats.dat)
    Var.emm <- emmeans::emmeans(m1.lmer, specs = ~ Nitrogen:Variety)
    Var.preds <- summary(Var.emm)
    Var.preds <- as.predictions.frame(Var.preds, predictions = "emmean", 
                                      se = "SE", interval.type = "CI", 
                                      interval.names = c("lower.CL", "upper.CL"))
  }

  if (exists("Var.preds"))
  {
    ## Check the class and validity of the alldiffs object
    is.predictions.frame(Var.preds)
    validPredictionsFrame(Var.preds)
  }

asremlPlus documentation built on Aug. 21, 2025, 5:58 p.m.