Description Usage Arguments Value Author(s) References See Also Examples

Rank responses of a single response question or a multiple response question under the Bayesian framework according to the loss function in Method 3 of Wang and Huang (2004).

1 |

`data` |
A m x n matrix dij, where dij = 0 or 1. If the ith respondent selects the jth response, then dij = 1, otherwise dij = 0. |

`response.number` |
The number of the responses. |

`prior.parameter` |
The parameter vector of the Dirichlet prior distribution, where the vector dimension is 2^response.number. |

`e` |
A cut point used in the loss function which depends on the economic costs. |

The rank.L2R returns the estimated probabilities of the responses being selected in the first line and the ranks of the responses in the second line.

Hsiuying Wangwang@stat.nctu.edu.tw,Yu-Chun Linrestart79610@hotmail.com

Wang, H. and Huang, W. H. (2014). Bayesian Ranking Responses in Multiple Response Questions. Journal of the Royal Statistical Society: Series A (Statistics in Society), 177, 191-208.

`rank.btmm`

,`rank.btnr`

,`rank.btqn`

,`rank.LN`

,`rank.gs`

,`rank.wald`

1 2 3 4 5 6 7 8 9 10 11 12 13 14 | ```
## This is an example to rank three responses in a multiple response
## question when the number of respondents is 1000 and the value e
## is 0.15. In this example, we do not use a real data, but generate
## data in the first three lines.
A <-sample.int(2,1000,replace=TRUE,prob=c(0.37,0.63))-1
B <-sample.int(2,1000,replace=TRUE,prob=c(0.71,0.29))-1
C <-sample.int(2,1000,replace=TRUE,prob=c(0.22,0.78))-1
D <-cbind(A,B,C)
data <-matrix(D,nrow=1000,ncol=3)
## or upload the true data
response.number <-3
prior.parameter <- c(5,98,63,7,42,7,7,7)
e <- 0.15
rank.L2R(data,response.number,prior.parameter,e)
``` |

Embedding an R snippet on your website

Add the following code to your website.

For more information on customizing the embed code, read Embedding Snippets.