# Power calculations for one and two sample t tests with unequal sample size

### Description

Compute power of test, or determine parameters to obtain target power for equal and unequal sample sizes.

### Usage

1 2 3 4 |

### Arguments

`n` |
Number of observations (per group) |

`delta` |
True difference in means |

`sd` |
Standard deviation |

`sig.level` |
Significance level (Type I error probability) |

`power` |
Power of test (1 minus Type II error probability) |

`ratio` |
The ratio n2/n1 between the larger group and the smaller group. Should be a value equal to or greater than 1 since n2 is the larger group. Defaults to 1 (equal group sizes) |

`sd.ratio` |
The ratio sd2/sd1 between the standard deviations in the larger group and the smaller group. Defaults to 1 (equal standard deviations in the two groups) |

`type` |
Type of t test |

`alternative` |
One- or two-sided test |

`df.method` |
Method for calculating the degrees of default. Possibilities are welch (the default) or classical. |

`strict` |
Use strict interpretation in two-sided case |

### Details

Exactly one of the parameters `n`

, `delta`

, `power`

, `sd`

, `sig.level`

, `ratio`

`sd.ratio`

must be passed as NULL,
and that parameter is determined from the others. Notice that the last two have non-NULL defaults
so NULL must be explicitly passed if you want to compute them.

If `strict = TRUE`

is used, the power will include the probability
of rejection in the opposite direction of the true effect, in the
two-sided case. Without this the power will be half the
significance level if the true difference is zero.

### Value

Object of class `power.htest`

, a list of the arguments (including the computed one)
augmented with `method`

and `note`

elements.

### Note

`uniroot`

is used to solve power equation for unknowns, so you may
see errors from it, notably about inability to bracket the root
when invalid arguments are given.

### Author(s)

Claus Ekstrom claus@rprimer.dk

### See Also

`power.prop.test`

### Examples

1 | ```
power.t.test(delta=300, sd=450, power=.8, ratio=4)
``` |