Performs a sensitivity analysis when planning sample size from the Accuracy in Parameter Estimation Perspective for the unstandardized regression coefficient.

1 2 3 4 5 6 | ```
ss.aipe.rc.sensitivity(True.Var.Y = NULL, True.Cov.YX = NULL,
True.Cov.XX = NULL, Estimated.Var.Y = NULL, Estimated.Cov.YX = NULL,
Estimated.Cov.XX = NULL, Specified.N = NULL, which.predictor = 1,
w = NULL, Noncentral = FALSE, Standardize = FALSE, conf.level = 0.95,
degree.of.certainty = NULL, assurance=NULL, certainty=NULL,
G = 1000, print.iter = TRUE)
``` |

`True.Var.Y` |
Population variance of the dependent variable ( |

`True.Cov.YX` |
Population covariances vector between the |

`True.Cov.XX` |
Population covariance matrix of the |

`Estimated.Var.Y` |
Estimated variance of the dependent variable ( |

`Estimated.Cov.YX` |
Estimated covariances vector between the p predictor variables and the dependent
variable ( |

`Estimated.Cov.XX` |
Estimated Population covariance matrix of the |

`Specified.N` |
Directly specified sample size (instead of using |

`which.predictor` |
identifies which of the |

`w` |
desired confidence interval width for the regression coefficient of interest |

`Noncentral` |
specify with a |

`Standardize` |
specify with a |

`conf.level` |
desired level of confidence for the computed interval (i.e., 1 - the Type I error rate) |

`degree.of.certainty` |
degree of certainty that the obtained confidence interval will be sufficiently narrow (i.e., the probability that the observed interval will be no larger than desired). |

`assurance` |
an alias for |

`certainty` |
an alias for |

`G` |
the number of generations/replication of the simulation student within the function |

`print.iter` |
specify with a |

Direct specification of `True.Rho.YX`

and `True.RHO.XX`

is necessary, even if one is interested in
a single regression coefficient, so that the covariance/correlation structure can be specified when
when the simulation student within the function runs.

`Results ` |
a matrix containing the empirical results from each of the |

`Specifications ` |
a list of the input specifications and the required sample size |

`Summary.of.Results` |
summary values for the results of the sensitivity analysis (simulation study) given the input specification |

Note that when `True.Rho.YX=Estimated.Rho.YX`

and `True.RHO.XX=Estimated.RHO.XX`

,
the results are not literally from a sensitivity analysis, rather the function performs a standard simulation
study. A simulation study can be helpful in order to determine if the sample size procedure
under or overestimates necessary sample size.

See `ss.aipe.reg.coef.sensitivity`

in MBESS for more details.

Ken Kelley (University of Notre Dame; KKelley@ND.Edu)

Kelley, K. & Maxwell, S. E. (2003). Sample size for Multiple Regression: Obtaining regression
coefficients that are accuracy, not simply significant. *Psychological Methods, 8*, 305–321.

`ss.aipe.reg.coef.sensitivity`

, `ss.aipe.src.sensitivity`

,

Questions? Problems? Suggestions? Tweet to @rdrrHQ or email at ian@mutexlabs.com.

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