pairedCVLDT: Paired comparisons on data.tables
In VinLaflamme/muCoVL: What the package does (short line)

Description Usage Arguments Value References Examples

Calculates paired comparisons for a factor on a data.table

1 2	pairedCVLDT(dataT, facF, otherF = NULL, aggF = NULL, DV, subF, aovv = NULL, tDec = 2, pDec = 3, pCut = 0.001, dDec = 3)

`dataT`	The data table
`facF`	The name of the column containing the factor on which the comparisons are operated.
`otherF`	Any other factors in the ANOVA design. Useful for simple effects. Vector of column names or comma separated string of column names.
`aggF`	Factors to aggregate on. Useful when decomposing main effects. Vector of column names or comma separated string of column names.
`DV`	Name of the column containing the dependant variable.
`subF`	Name of the column containing the subject code.
`aovv`	(optional) aov object
`tDec`	Number of decimals for the t statistic
`pDec`	Number of decimals for the p value(s)
`pCut`	Cutting point for the p value
`dDec`	Number of decimals for Cohen's d

Augmented data.table with the means, t tests and effect sizes.

Lakens, D. (2013). Calculating and reporting effect sizes to facilitate cumulative science: a practical primer for t-tests and ANOVAs. Frontiers in Psychology, 4.

data("donn_ag",package="muCoVL")
dataT<-donn_ag
facF<-"Trial_Block"
otherF<-"Group,dist"
aggF<-"dur"
DV<-"relE"
subF<-"sub"
pairedCVLDT(dataT,facF,otherF,aggF,DV,subF)