# Plots the optimum k measures per individual (or group), based upon a fixed total researcher effort.

### Description

Given a fixed researcher effort (e.g., total number of assays able to be run), this function plots the optimum `k`

measurements per individual to use in order to obtain the smallest confidence interval at an expected intraclass correlation coefficient (ICC) estimate. The results are depicted graphically, showing the tradeoff in confidence interval width with changing `k`

.

### Usage

1 2 |

### Arguments

`est.type` |
character string of either |

`e` |
the total effort ( |

`ICC` |
expected intraclass correlation coefficient |

`x` |
column name of |

`y` |
column name of |

`data` |
a |

`alpha` |
the alpha level to use when estimating the confidence interval |

### Details

More than one `e`

may be given. In this case, the graphical result portrays multiple lines - each representing a different `e`

When `est.type="pilot"`

, the function automatically generates an effort 10 percent larger and smaller than the calculated effort from the pilot data.

### Author(s)

Matthew Wolak matthewwolak@gmail.com

### See Also

`Nest`

### Examples

1 2 3 4 5 6 | ```
#Example 1
effort(est.type="h", e=c(30, 60, 120), ICC=0.2)
#Example 2
data(ChickWeight)
effort(est.type="p", x=Chick, y=weight, data=ChickWeight)
``` |