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asremlPlus (version 4.3-19)

recalcLSD.alldiffs: Adds or recalculates the LSD.frame that is a component of an alldiffs.object.

Description

Given an alldiffs.object, adds or recalculate its LSD.frame. N.B. No changes are made to the error.intervals --- use redoErrorIntervals.alldiffs to modify both the error.intervals and the LSD.frame.

Usage

# S3 method for alldiffs
recalcLSD(alldiffs.obj, LSDtype = "overall", LSDsupplied = NULL, 
          LSDby = NULL, LSDstatistic = "mean", LSDaccuracy = "maxAbsDeviation", 
          alpha = 0.05, ...)

Arguments

alldiffs.obj
LSDtype

A character string that can be overall, factor.combinations, per.prediction or supplied. It determines whether the values stored in an LSD.frame are (i) the overall number of pairwise comparisons, c, and the minimum, mean, maximum and accuracy of all pairwise LSDs, (ii) the number of pairwise comparisons, c, and the minimum, mean, maximum and acuracy for the pairwise LSDs for each factor.combination, unless there is only one prediction for a factor.combination, when notional LSDs are calculated, (iii) the per.prediction number of pairwise comparisons, c, and the minimum, mean, maximum and accuracy, based, for each prediction, on all pairwise differences involving that prediction, or (iv) supplied values of the LSD, specified with the LSDsupplied argument; these values are to be placed in the assignedLSD column of the LSD.frame stored in an alldiffs.object so that they can be used in LSD calculations. See LSD.frame for further information on the calculation of the values in this data.frame.

LSDsupplied

A data.frame or a named numeric containing a set of LSD values that correspond to the observed combinations of the values of the LSDby variables in the predictions.frame or a single LSD value that is an overall LSD. If a data.frame, it may have a column for each LSDby variable and a column of LSD values or a single column of LSD values with rownames being the combinations of the observed combinations of the values of the LSDby variables. Any name can be used for the column of LSD values; assignedLSD is sensible, but not obligatory. Otherwise, a numeric containing the LSD values, each of which is named for the observed combination of the values of the LSDby variables to which it corresponds. (Applying the function dae::fac.combine to the predictions component is one way of forming the required combinations for the (row) names.) The values supplied will be incorporated into assignedLSD column of the LSD.frame stored as the LSD component of the alldiffs.object.

LSDby

A character (vector) of variables names, being the names of the factors or numerics in the classify for each combination of which a mean LSD, minLSD and maxLSD is stored in the LSD component of the alldiffs.object when LSDtype is factor.combinatons.

LSDstatistic

A character nominating one of minmum, q10, median, mean, q90 or maximum as the value(s) to use in the calculation of the halfLeastSignificant error.intervals. Here q10 and q90 indicate the sample quantiles corresponging to probabilities of 0.1 and 0.9, the function quantile being used to obtain them. The values of the nominated statistics are stored in the column named assignedLSD in an LSD.frame. LSDstatistic is ignored if it is not NULL.

LSDaccuracy

A character nominating one of maxAbsDeviation, maxDeviation, q90Deviation or RootMeanSqDeviation as the statistic to be calculated as a measure of the accuracy of assignedLSD. The option q90Deviation produces the sample quantile corresponding to a probability of 0.90. The deviations are the differences between the LSDs used in calculating the LSD statistics and each assigned LSD and the accuracy is expressed as a proportion of the assigned LSD value. The calculated values are stored in the column named accuracyLSD in an LSD.frame.

alpha

The significance level for an LSD to compare a pair of predictions. It is stored as an attribute to the alldiffs.object.

further arguments passed to allDifferences.data.frame; attributes tranform.power, offset and scale cannot be passed.

Value

An alldiffs.object with components predictions, vcov, differences, p.differences sed, LSD and, if present in alldiffs.obj, backtransforms.

See Also

asremlPlus-package, as.alldiffs, sort.alldiffs, subset.alldiffs, print.alldiffs, renewClassify.alldiffs, exploreLSDs.alldiffs, redoErrorIntervals.alldiffs, plotPredictions.data.frame, predictPlus.asreml, predictPresent.asreml

Examples

Run this code
# NOT RUN {
data(WaterRunoff.dat)

##Use asreml to get predictions and associated statistics

# }
# NOT RUN {
asreml.options(keep.order = TRUE) #required for asreml-R4 only
current.asr <- asreml(fixed = pH ~ Benches + (Sources * (Type + Species)), 
                      random = ~ Benches:MainPlots,
                      keep.order=TRUE, data= WaterRunoff.dat)
current.asrt <- as.asrtests(current.asr, NULL, NULL)
TS.diffs <- predictPlus(classify = "Sources:Type", 
                        asreml.obj = current.asr, 
                        wald.tab = current.asrt$wald.tab, 
                        present = c("Sources", "Type", "Species"))
# }
# NOT RUN {
## Use lmeTest and emmmeans to get predictions and associated statistics

if (requireNamespace("lmerTest", quietly = TRUE) & 
    requireNamespace("emmeans", quietly = TRUE))
{
  m1.lmer <- lmerTest::lmer(pH ~ Benches + (Sources * (Type + Species)) + 
                              (1|Benches:MainPlots),
                            data=na.omit(WaterRunoff.dat))
  TS.emm <- emmeans::emmeans(m1.lmer, specs = ~ Sources:Species)
  TS.preds <- summary(TS.emm)
  den.df <- min(TS.preds$df, na.rm = TRUE)
  ## Modify TS.preds to be compatible with a predictions.frame
  TS.preds <- as.predictions.frame(TS.preds, predictions = "emmean", 
                                   se = "SE", interval.type = "CI", 
                                   interval.names = c("lower.CL", "upper.CL"))
  
  ## Form an all.diffs object and check its validity
  els <- as.numeric(rownames(TS.preds))
  TS.vcov <- vcov(TS.emm)[els,els]
  TS.diffs <- allDifferences(predictions = TS.preds, classify = "Sources:Species", 
                             vcov = TS.vcov, tdf = den.df)
  validAlldiffs(TS.diffs)
}  

## Plot p-values for predictions obtained using asreml or lmerTest
if (exists("TS.diffs"))
{
  ##Recalculate the LSD values for predictions obtained using asreml or lmerTest  
  TS.diffs <- recalcLSD.alldiffs(TS.diffs, LSDtype = "factor.combinations", 
                                 LSDby = "Sources")
}
# }

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