# use the Pocock-Simon or Taves algorithm for computing covariate-adaptive 'minimization' allocations for a clinical trial

### Description

use the Pocock-Simon or Taves algorithm for computing covariate-adaptive 'minimization' allocations for a clinical trial

### Usage

1 2 | ```
minimizePocSim(df, features, trtvec, obsdf, trttab, f = function(x, y) sum(abs(x + 1 - y)))
minimizeTaves(df, features, trtvec, obsdf, trttab)
``` |

### Arguments

`df` |
a data frame with columns corresponding to covariates rows corresponding to subjects |

`features` |
character vector of covariates to use |

`trtvec` |
vector of assignments made so far |

`obsdf` |
data frame for incoming observation, with values for
all components enumerated in |

`trttab` |
table of treatment ratios |

`f` |
score that determines impending allocation |

### Details

These functions are generally not called directly. See the vignette; if supplied as the method slot of a MinimizationDesc object the appropriate data are assembled as arguments to these functions.

### Value

a treatment code

### Examples

1 2 | ```
new("MinimizationDesc", treatments=c(A=1L, B=1L), method=minimizePocSim,
type="Minimization", featuresInUse="sex")
``` |