View source: R/CrossFittedR2.R

CF_Rsq.measure | R Documentation |

Function to calculate the Rsq function as a total effect size measure for mediation effect using cross-fitted estimation

```
CF_Rsq.measure(
Y,
M,
Covar = NULL,
X,
iter.max = 3,
nsis = NULL,
first.half = TRUE,
seed = 2022,
tune = c("aic", "bic"),
penalty = c("MCP", "lasso")
)
```

`Y` |
vector of the outcome of interest; outcome has to follow a Gaussian distribution. |

`M` |
matrix of putative mediators |

`Covar` |
covariates matrix |

`X` |
vector of the independent variable of interest, e.g. environmental variable |

`iter.max` |
Maximum number of iterations used in iSIS, default = 3 (details see the SIS package). |

`nsis` |
Number of predictors recruited by iSIS, default = NULL |

`first.half` |
TRUE: split sample into two halves by the order in the dataset. FALSE: randomly split samples into halves, default = TRUE. |

`seed` |
Random seed used for sample splitting, default = 2022. |

`tune` |
Method for tuning the regularization parameter of the penalized likelihood subproblems and of the final model selected by (i)SIS. Options include tune = 'bic' and tune = 'aic'. |

`penalty` |
The penalty to be applied in the regularized likelihood subproblems. 'MCP', and 'lasso' are provided. 'MCP' is recommended. |

Output Vector consisting of Rsq mediated(Rsq.mediated), Lower confidence bound constructed by the asymptotic variance (CI_asym_low), Upper confidence bound constructed by the asymptotic variance (CI_asym_up), Lower confidence bound constructed by the conservative variance (CI_cons_low), Upper confidence bound constructed by the conservative variance (CI_cons_up), number of selected mediators in subsample 1 (pab1), number of selected mediators in subsample 2 (pab2), and the Rsq that used to calculate the Rsq measure: variance of outcome explained by mediator (Rsq.YM), variance of outcome explained by the independent variable (Rsq.YX), and variance of outcome explained by mediator and independent variable (Rsq.YMX); Sample Size in analysis (Sample Size)

Name of selected mediators in subsample 1 (select1)

Name of selected mediators in subsample 2 (select2)

```
{
data(example)
attach(example)
CF_Rsq.measure(Y=Y, M=M, X=X, tune = "bic", penalty = "MCP")
}
```

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