Description Usage Arguments See Also Examples

Calculating effect size (Cohen's d) of paired two-sample t test

1 2 |

`md` |
mean difference (e.g., mean(x-y)) |

`sd` |
standard deviation of mean differences (e.g., sd(x-y)) |

`n` |
number of paires |

`t` |
t statistic |

`se` |
standard error of mean differences |

`df` |
degree of freedom |

`alternative` |
The test is two sided or one sided |

1 2 3 4 5 6 7 8 9 10 11 | ```
## md, sd -> d
ES.t.paired(md=-0.08062384,sd=1.401886)
## md,se -> d
ES.t.paired(md=-0.08062384,se=0.1982566,n=50)
## t, df -> d
ES.t.paired(t=-0.4067,df=49)
## t, n -> d
ES.t.paired(t=-0.4067,n=50)
``` |

```
effect size (Cohen's d) of paired two-sample t test
d = 0.05751098
alternative = two.sided
NOTE: The alternative hypothesis is md != 0
small effect size: d = 0.2
medium effect size: d = 0.5
large effect size: d = 0.8
effect size (Cohen's d) of paired two-sample t test
d = 0.05751099
alternative = two.sided
NOTE: The alternative hypothesis is md != 0
small effect size: d = 0.2
medium effect size: d = 0.5
large effect size: d = 0.8
effect size (Cohen's d) of paired two-sample t test
d = 0.0581
alternative = two.sided
NOTE: The alternative hypothesis is md != 0
small effect size: d = 0.2
medium effect size: d = 0.5
large effect size: d = 0.8
effect size (Cohen's d) of paired two-sample t test
d = 0.0581
alternative = two.sided
NOTE: The alternative hypothesis is md != 0
small effect size: d = 0.2
medium effect size: d = 0.5
large effect size: d = 0.8
```

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