View source: R/ci_measures_of_scale.R

ci_var | R Documentation |

This function calculates CIs for the population variance.

```
ci_var(
x,
probs = c(0.025, 0.975),
type = c("chi-squared", "bootstrap"),
boot_type = c("bca", "perc", "stud", "norm", "basic"),
R = 9999L,
seed = NULL,
...
)
```

`x` |
A numeric vector. |

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

`type` |
Type of CI. One of |

`boot_type` |
Type of bootstrap CI. Only used for |

`R` |
The number of bootstrap resamples. Only used for |

`seed` |
An integer random seed. Only used for |

`...` |
Further arguments passed to |

By default, classic CIs are calculated based on the chi-squared distribution, assuming normal distribution (see Smithson). Bootstrap CIs are also available (default: "bca"). We recommend them for the non-normal case.

The `stud`

(bootstrap t) bootstrap uses the standard error of the sample variance
given in Wilks.

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.

S.S. Wilks (1962), Mathematical Statistics, Wiley & Sons.

`ci_sd()`

```
x <- 1:100
ci_var(x)
ci_var(x, type = "bootstrap", R = 999) # Use larger R
```

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