as.mudfold | R Documentation |
This function calculates the MUDFOLD statistics for data whose columns are assumed to be ranked to the order they are provided. The resulting object from the as.mudfold
function is an object of S3 class "mdf"
, for which generic functions print
, summary
, and plot
are available.
as.mudfold(data,estimation="rank")
data |
: A binary |
estimation |
: This argument controls the nonparametric estimation method for person locations. By deafult this argument equals to |
The function as.mudfold
calculates MUDFOLD statistics for a given scale. Descriptive statistics, observed errors, expected errors, scalability coefficients, iso statistic values, are calculated for items and the scale. The user can obtain a summary table for the given scale with the summary
function which is designed for "mdf"
class objects.
The function as.mudfold
returns a list with the same components as the mudfold
function except the information that concerns the item selection algorithm. The list contains the following:
CALL |
A list where its components provide information for the function call. |
CHECK |
A list where its components provide information from the data checking step. |
DESCRIPTIVES |
A list with descriptive statistics for the |
MUDFOLD_INFO |
A list with three main components. The first component is called |
Spyros E. Balafas (auth.), Wim P. Krijnen (auth.), Wendy J. Post (contr.), Ernst C. Wit (auth.)
Maintainer: Spyros E. Balafas (s.balafas@rug.nl)
W.H. Van Schuur.(1984). Structure in Political Beliefs: A New Model for Stochastic Unfolding with Application to European Party Activists. CT Press.
W.J. Post. (1992). Nonparametric Unfolding Models: A Latent Structure Approach. M & T series. DSWO Press.
W.J. Post. and T.AB. Snijders. (1993).Nonparametric unfolding models for dichotomous data. Methodika.
M.S. Johnson. (2006). Nonparametric Estimation of Item and Respondent Locations from Unfolding-type Items. Psychometrica
mudfold
## Not run: ## pick a number for setting the seed n.seed <- 11 ## Simulate an unfolding scale simulation <- mudfoldsim(N=6, n=100, seed=n.seed) ## get the data dat <- simulation$dat ## true order true_order <- simulation$true_ord ## check MUDFOLD statistics for the random simulated rank order mud_stats1 <- as.mudfold(dat) # get the summary summary(mud_stats1) ## check MUDFOLD statistics for the true item rank order mud_stats2 <- as.mudfold(dat[,true_order]) # get the summary for the true item rank order summary(mud_stats2) ## End(Not run)
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.