mxGREMLDataHandler {OpenMx} | R Documentation |

This function takes a dataframe or matrix and uses it to setup the 'y' and 'X' matrices for a GREML analysis; this includes trimming out `NA`

s from 'X' and 'y.' The result is a matrix the first column of which is the 'y' vector, and the remaining columns of which constitute 'X.'

mxGREMLDataHandler(data, yvars=character(0), Xvars=list(), addOnes=TRUE, blockByPheno=TRUE, staggerZeroes=TRUE)

`data` |
Either a dataframe or matrix, with column names, containing the variables to be used as phenotypes and covariates in 'y' and 'X,' respectively. |

`yvars` |
Character vector. Each string names a column of the raw dataset, to be used as a phenotype. |

`Xvars` |
A list of data column names, specifying the covariates to be used with each phenotype. The list should have the same length as argument |

`addOnes` |
Logical; should lead columns of ones (for the regression intercepts) be adhered to the covariates when assembling the 'X' matrix? Defaults to |

`blockByPheno` |
Logical; relevant to polyphenotype analyses. If |

`staggerZeroes` |
Logical; relevant to polyphenotype analyses. If |

For a monophenotype analysis (only), argument `Xdata`

can be a character vector. In a polyphenotype analysis, if the same covariates are to be used with all phenotypes, then `Xdata`

can be a list of length 1.

Note the synergy between the output of `mxGREMLDataHandler()`

and arguments `dataset.is.yX`

and `casesToDropFromV`

to `mxExpectationGREML()`

.

If the dataframe or matrix supplied for argument `data`

has *n* rows, and argument `yvars`

is of length *p*, then the resulting 'y' and 'X' matrices will have *np* rows. Then, if either matrix contains any `NA`

's, the rows containing the `NA`

's are trimmed from both 'X' and 'y' before being returned in the output (in which case they will obviously have fewer than *np* rows). Function `mxGREMLDataHandler()`

reports which rows of the full-size 'X' and 'y' were trimmed out due to missing observations. These row indices can be provided as argument `casesToDropFromV`

to `mxExpectationGREML()`

.

A list with these two components:

`yX` |
Numeric matrix. The first column is the phenotype vector, 'y,' while the remaining columns constitutethe 'X' matrix of covariates. If this matrix is used as the raw dataset for a model, then the model's GREML expectation can be constructed with |

`casesToDrop` |
Numeric vector. Contains the indices of the rows of the 'y' and 'X' that were dropped due to containing |

The OpenMx User's guide can be found at http://openmx.ssri.psu.edu/documentation.

For more information generally concerning GREML analyses, including a complete example, see `mxExpectationGREML()`

. More information about the OpenMx package may be found here.

dat <- cbind(rnorm(100),rep(1,100)) colnames(dat) <- c("y","x") dat[42,1] <- NA dat[57,2] <- NA dat2 <- mxGREMLDataHandler(data=dat, yvars="y", Xvars=list("x"), addOnes = FALSE) str(dat2)

[Package *OpenMx* version 2.7.9 Index]