Description Usage Arguments Details Value Author(s) Examples

Regression coefficients for a normal linear model are be calculated, using a pre-built sufficient summary statistic matrix that contains the second moments between all the variables of (potential) interest.

1 | ```
lm.moments2(xtx, leftvar, rightvars, n = NULL)
``` |

`xtx` |
a matrix of second moments, typically built using |

`leftvar` |
name of the response variable (the left hand side of the formula). |

`rightvars` |
name(s) of the explanatory variables (the right hand side of the formula). |

`n` |
sample size, only needed if there is not a single intercept for all individuals. |

Non-identifiable variables in `rightvars`

are removed, with
preference for keeping variables that occur earlier rather than later
in `rightvars`

.

A list with slots for the effect size estimates, standard errors, and a precision matrix.

This function is just a wrapper for calling `est.moments2`

with
`scale = NULL`

.

Toby Johnson Toby.x.Johnson@gsk.com

1 2 3 4 5 6 7 8 | ```
data(mthfrex)
xtx <- make.moments2(mthfr.params, c("SBP", "DBP", "SexC", "Age"), mthfrex)
lm.moments2(xtx, "SBP", c("ONE", "rs6668659_T", "rs4846049_T",
"rs1801133_G", "SexC", "Age"))
## Compare against results from lm
## Note have to use coded alleles in original data
lm(SBP ~ rs6668659_G+rs4846049_G+rs1801133_A+Sex+Age, data = mthfrex$data)
## Note in results Sex factor coded differently than SexC
``` |

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