ci_f_ncp | R Documentation |

Based on the inversion principle, parametric CIs for the non-centrality parameter (NCP) Delta of the F distribution are calculated. To keep the input interface simple, we do not provide bootstrap CIs here.

```
ci_f_ncp(x, df1 = NULL, df2 = NULL, probs = c(0.025, 0.975))
```

`x` |
The result of |

`df1` |
The numerator df. Only used if |

`df2` |
The denominator df. Only used if |

`probs` |
Lower and upper probabilities, by default |

A positive lower `(1 - \alpha) \cdot 100\%`

-confidence limit for the NCP goes
hand-in-hand with a significant F test at level `\alpha`

.
According to `stats::pf()`

, the results might be unreliable for very large F values.

An object of class "cint", see `ci_mean()`

for details.

Smithson, M. (2003). Confidence intervals. Series: Quantitative Applications in the Social Sciences. New York, NY: Sage Publications.

`ci_rsquared()`

```
fit <- lm(Sepal.Length ~ ., data = iris)
ci_f_ncp(fit)
ci_f_ncp(fit, probs = c(0.05, 1))
```

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