complr function

Indices from a (dataset of) Multilevel Composition(s)

Compute sets of compositions and log ratio transformation for multilevel compositional data

complr(data, parts, sbp = NULL, total = 1, idvar = NULL, transform = "ilr")

Arguments

• data: A data.frame or data.table

  containing data of all variables used in the analysis. It must include a composition and a ID variable. Required.

• parts: A character vector specifying the names of compositional variables to be used.

• sbp: A signary matrix indicating sequential binary partition.

• total: A numeric value of the total amount to which the compositions should be closed. Default is 1.

• idvar: Only for multilevel data, a character string specifying the name of the variable containing IDs.

• transform: A character value naming a log ratio transformation to be applied on compositional data. Can be either "ilr" (isometric logratio), "alr" (additive logratio), or "clr" (centered logratio). Default is "ilr".

Returns

A complr object with at least the following elements. - comp: A vector of class acomp representing one closed composition or a matrix of class acomp representing multiple closed compositions each in one row.

• between_comp: A vector of class acomp representing one closed between-person composition or a matrix of class acomp representing multiple closed between-person compositions each in one row.

• within_comp: A vector of class acomp representing one closed within-person composition or a matrix of class acomp representing multiple closed within-person compositions each in one row.

• logratio: Log ratio transform of composition.

• between_logratio: Log ratio transform of between-person composition.

• within_logratio: Log ratio transform of within-person composition.

• data: The user's dataset or imputed dataset if the input data contains zeros.

• transform: Type of transform applied on compositional data.

• parts: Names of compositional variables.

• idvar: Name of the variable containing IDs.

• total: Total amount to which the compositions is closed.

Details

The ilr-transform maps the D-part compositional data from the simplex into non-overlapping subgroups in the (D-1)-dimension Euclidean space isometrically by using an orthonormal basis, thereby preserving the compositional properties and yielding a full-rank covariance matrix. ilr transformation should be preferred. However, the alr and clr are alternatives. The alr-transform maps a D-part composition in the Aitchison-simplex non-isometrically to a (D-1)-dimension Euclidian vectors, commonly treating the last part as the common denominator of the others. alr transformation does not rely on distance which breaks the constraint of compositional data. clr-transform maps a D-part composition in the Aitchison-simplex isometrically to a D-dimensional Euclidian vector subspace. clr transformation is not injetive, resulting in singular covariance matrices.

Examples

cilr <- complr(data = mcompd,
                parts = c("TST", "WAKE", "MVPA", "LPA", "SB"),
                idvar = "ID", total = 1440)
str(cilr)

calr <- complr(data = mcompd, sbp = sbp,
                parts = c("TST", "WAKE", "MVPA", "LPA", "SB"),
                idvar = "ID",
                transform = "alr")
str(calr)

cclr <- complr(data = mcompd, sbp = sbp,
                parts = c("TST", "WAKE", "MVPA", "LPA", "SB"),
                idvar = "ID",
                 transform = "clr")
str(cclr)

cilr_wide <- complr(data = mcompd[!duplicated(ID)], sbp = sbp,
                parts = c("TST", "WAKE", "MVPA", "LPA", "SB"))
str(cilr_wide)