`mv_harmonise_data.Rd`

Harmonise exposure and outcome for multivariable MR

mv_harmonise_data(exposure_dat, outcome_dat, harmonise_strictness = 2)

exposure_dat | Output from |
---|---|

outcome_dat | Output from |

harmonise_strictness | See the |

List of vectors and matrices required for mv analysis.

- exposure_beta
a matrix of beta coefficients, in which rows correspond to SNPs and columns correspond to exposures.

- exposure_se
is the same as

`exposure_beta`

, but for standard errors.- exposure_pval
the same as

`exposure_beta`

, but for p-values.- expname
A data frame with two variables,

`id.exposure`

and`exposure`

which are character strings.- outcome_beta
an array of effects for the outcome, corresponding to the SNPs in exposure_beta.

- outcome_se
an array of standard errors for the outcome.

- outcome_pval
an array of p-values for the outcome.

- outname
A data frame with two variables,

`id.outcome`

and`outcome`

which are character strings.