# sra: Compute the sequential rank agreement In SuperRanker: Sequential Rank Agreement

## Description

Compute the sequential rank agreement

## Usage

 ``` 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26``` ```sra(object, B, na.strings, nitems, type, epsilon = 0, ...) ## Default S3 method: sra(object, B, na.strings, nitems, type, epsilon = 0, ...) ## S3 method for class 'matrix' sra( object, B = 1, na.strings = NULL, nitems = nrow(object), type = c("sd", "mad"), epsilon = 0, ... ) ## S3 method for class 'list' sra( object, B = 1, na.strings = NULL, nitems = max(sapply(object, length)), type = c("sd", "mad"), epsilon = 0, ... ) ```

## Arguments

 `object` Either matrix where each column is a ranked list of items or a list of ranked lists of items. Elements are integers between 1 and the length of the lists. The lists should have the same length but censoring can be used by setting the list to zero from a point onwards. See details for more information. `B` An integer giving the number of randomization to sample over in the case of censored observations `na.strings` A vector of strings/values that represent missing values in addition to NA. Defaults to NULL which means only NA are censored values. `nitems` The total number of items in the original lists if we only have partial lists available. `type` The type of measure to use. Either sd (standard deviation - the default) or mad (median absolute deviance around the median) `epsilon` A non-negative numeric vector that contains the minimum limit in proportion of lists that must show the item. Defaults to 0. If a single number is provided then the value will be recycles to the number of items. `...` Arguments passed to methods.

## Value

A vector of the sequential rank agreement

## Author(s)

Claus Ekstrøm <ekstrom@sund.ku.dk> and Thomas A Gerds <tag@biostat.ku.dk>

## Examples

 ``` 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25``` ```mlist <- matrix(cbind(1:8,c(1,2,3,5,6,7,4,8),c(1,5,3,4,2,8,7,6)),ncol=3) sra(mlist) mlist <- matrix(cbind(1:8,c(1,2,3,5,6,7,4,8),c(1,5,3,4,2,8,7,6)),ncol=3) sra(mlist, nitems=20, B=10) alist <- list(a=1:8,b=sample(1:8),c=sample(1:8)) sra(alist) blist <- list(x1=letters,x2=sample(letters),x3=sample(letters)) sra(blist) ## censored lists are either too short clist <- list(x1=c("a","b","c","d","e","f","g","h"), x2=c("h","c","f","g","b"), x3=c("d","e","a")) set.seed(17) sra(clist,na.strings="z",B=10) ## or use a special code for missing elements Clist <- list(x1=c("a","b","c","d","e","f","g","h"), x2=c("h","c","f","g","b","z","z","z"), x3=c("d","e","a","z","z","z","z","z")) set.seed(17) sra(Clist,na.strings="z",B=10) ```

SuperRanker documentation built on Jan. 30, 2021, 1:06 a.m.