View source: R/oneway_ancova.R

power_oneway_ancova | R Documentation |

Compute power of ANCOVA omnibus test (power_oneway_ancova) or contrast (power_oneway_ancova) for one-way (single factor), between subjects designs.

power_oneway_ancova( n = NULL, mu = NULL, n_cov = 1, r2 = NULL, sd = 1, alpha_level = Superpower_options("alpha_level"), beta_level = NULL, round_up = TRUE, type = "exact" )

`n` |
Sample size in each condition. |

`mu` |
Vector specifying mean for each condition. |

`n_cov` |
Number of covariates. |

`r2` |
Coefficient of determination (r^2) of the combined covariates. |

`sd` |
Standard deviation for all conditions (residual SD without covariate adjustment). |

`alpha_level` |
Alpha level used to determine statistical significance. |

`beta_level` |
Type II error probability (power/100-1) |

`round_up` |
Logical indicator for whether to round up the sample size(s) to a whole number. Default is TRUE. |

`type` |
Sets the method for estimating power. "exact" will use the Shieh (2020) approach while "approx" will use the Keppel (1991) approach. |

dfs = degrees of freedom, N = Total sample size, n = Sample size per group/condition, n_cov = Number of covariates, mu = Mean for each condition, sd = Standard deviation, r2 = Coefficient of determination of combined covariates. alpha_level = Type 1 error probability, beta_level = Type 2 error probability, power = Power of test (1-beta_level\*100 type = Method (Shieh or Keppel) for estimating power

Keppel, G. (1991). Design and Analysis A Researcher's Handbook. 3rd Edition. Prentice Hall. Englewood Cliffs, New Jersey. See pages 323 - 324. Shieh, G. (2017). Power and sample size calculations for contrast analysis in ANCOVA. Multivariate behavioral research, 52(1), 1-11. Shieh, G. (2020). Power analysis and sample size planning in ANCOVA designs. Psychometrika, 85(1), 101-120.

# Example from Table 1 Shieh 2020 power_oneway_ancova(mu = c(400, 450, 500), n = c(21,21,21), r2 = .1^2, sd = 100)

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