Description Usage Arguments See Also Examples

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

1 2 3 |

`m1` |
mean of sample 1 |

`m2` |
mean of sample 2 |

`sd1` |
standard deviation of sample 1 |

`sd2` |
standard deviation of sample 2 |

`n1` |
number of observations in sample 1 |

`n2` |
number of observations in sample 2 |

`t` |
t statistic |

`se1` |
standard error of sample 1 |

`se2` |
standard error of sample 2 |

`df` |
degree of freedom |

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

1 2 3 4 5 6 7 8 9 10 11 12 13 14 | ```
## mean, sd, n -> d
ES.t.two(m1=13.5,m2=5.5,sd1=4.1833,sd2=3.02765,n1=14,n2=10)
## mean se, n -> d
ES.t.two(m1=13.5,m2=5.5,se1=1.118034,se2=0.9574271,n1=14,n2=10)
## t and n -> d
ES.t.two(n1=14,n2=10,t=5.4349)
## t, df and n -> d
ES.t.two(t = 5.4349, df = 21.982,n1=14,n2=10)
## t and df -> d (assume n1=n2)
ES.t.two(t = 5.4349, df = 21.982)
``` |

powerAnalysis documentation built on May 30, 2017, 3:50 a.m.

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