yuend | R Documentation |

The function `yuend`

performs Yuen's test on trimmed means for dependent samples. `Dqcomhd`

compares the quantiles of the marginal distributions associated with two dependent groups via hd estimator. Tied values are allowed.
`dep.effect`

computes various effect sizes and confidence intervals for two dependent samples (see Details).

```
yuend(x, y, tr = 0.2, ...)
Dqcomhd(x, y, q = c(1:9)/10, nboot = 1000, na.rm = TRUE, ...)
dep.effect(x, y, tr = 0.2, nboot = 1000, ...)
```

`x` |
an numeric vector of data values (e.g. for time 1). |

`y` |
an numeric vector of data values (e.g. for time 2). |

`tr` |
trim level for the means. |

`q` |
quantiles to be compared. |

`nboot` |
number of bootstrap samples. |

`na.rm` |
whether missing values should be removed. |

`...` |
currently ignored. |

The test statistic is a paired samples generalization of Yuen's independent samples t-test on trimmed means.

`dep.effect`

computes the following effect sizes:

AKP: robust standardized difference similar to Cohen's d

QS: Quantile shift based on the median of the distribution of difference scores,

QStr: Quantile shift based on the trimmed mean of the distribution of X-Y

SIGN: P(X<Y), probability that for a random pair, the first is less than the second.

`yuend`

returns an object of class `"yuen"`

containing:

`test` |
value of the test statistic (t-statistic) |

`p.value` |
p-value |

`conf.int` |
confidence interval |

`df` |
degress of freedom |

`diff` |
trimmed mean difference |

`call` |
function call |

`Dqcomhd`

returns an object of class `"robtab"`

containing:

`partable` |
parameter table |

`dep.effect`

returns a matrix with the null value of the effect size, the estimated effect size, small/medium/large conventions, and lower/upper CI bounds.

Wilcox, R. (2012). Introduction to Robust Estimation and Hypothesis Testing (3rd ed.). Elsevier.

`yuen`

, `qcomhd`

```
## Cholesterol data from Wilcox (2012, p. 197)
before <- c(190, 210, 300,240, 280, 170, 280, 250, 240, 220)
after <- c(210, 210, 340, 190, 260, 180, 200, 220, 230, 200)
yuend(before, after)
set.seed(123)
Dqcomhd(before, after, nboot = 200, q = c(0.25, 0.5, 0.75))
set.seed(123)
dep.effect(before, after)
```

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