# rank.wald: Rank responses based on the Wald test In RankResponse: Ranking Responses in a Single Response Question or a Multiple Response Question

## Description

Rank responses of a single response question or a multiple response question by the Wald test procedure.

## Usage

 `1` ```rank.wald(data, alpha, type=2) ```

## Arguments

 `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. `alpha` The significance level used in the Wald test. `type` type=1 for a single response question ;type=2 for a multiple response question .

## Value

The rank.wald returns the estimated probabilities of the responses being selected and the ranks of the responses by the Wald trest procedure.

## Author(s)

Hsiuying Wang[email protected],Yu-Chun Lin[email protected]

## References

Wang, H. (2008). Ranking Responses in Multiple-Choice Questions. Journal of Applied Statistics, 35, 465-474.

`rank.btmm`,`rank.btnr`,`rank.btqn`,`rank.L2R`,`rank.LN`,`rank.gs`
 ``` 1 2 3 4 5 6 7 8 9 10 11``` ```## This is an example to rank three responses in a multiple response question when ## the number of respondents is 1000 and the significance level is 0.05. 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(0.21,0.79))-1 B <-sample.int(2,1000,replace=TRUE,prob=c(0.81,0.19))-1 C <-sample.int(2,1000,replace=TRUE,prob=c(0.62,0.28))-1 D <-cbind(A,B,C) data <-matrix(D,nrow=1000,ncol=3) ## or upload the true data alpha<-0.05 rank.wald(data,alpha,2) ```