lwscreen {crank} | R Documentation |

## Impute ranks using the existing values of rankings

### Description

Completes a matrix with missing ranks for the values maximally and minimally consistent with existing values using the Lim-Wolfe procedure

### Usage

```
lwscreen(x,scrtest="lw.FriedmanTest")
```

### Arguments

`x` |
A matrix of ranks that may contain ties and NAs. Columns represent objects ranked and rows represent ranking methods. |

`scrtest` |
What test to use to determine the maximally and minimally consistent imputed values. |

### Details

‘lwscreen’ calls ‘fillArows’ to impute the missing ranks in the matrix ‘x’. It then applies ‘scrtest’ to all the matrices returned and finds the minimum and maximum values. See Lim and Wolfe (2002) for details of the algorithm.

The algorithm for finding the maximally consistent and inconsistent rank imputations is extremely computer intensive, creating large numbers of permuted matrices when tied ranksums or multiple rows with the same number of missing values are encountered. The APA election example in Lim and Wolfe (2002) is beyond the capability of the average PC in the present implementation.

### Value

The maximal and minimal statistics and p values for the list of completed rank matrices obtained.

### Author(s)

Jim Lemon

### References

Lim, D.H. & Wolfe, D.A. (2002) An efficient alternative to average ranks for testing with incomplete ranking data. Biometrical Journal, 43(2): 187-206.

### See Also

lw.FriedmanTest, listBuilder, fillArows

### Examples

```
# The first example matrix from Lim and Wolfe (2002)
lwmat<-matrix(c(3,1,2,4,NA,2,1,NA,2,NA,1,NA),nrow=3,byrow=TRUE)
lwscreen(lwmat)
```

*crank*version 1.1-2 Index]