534 research outputs found
Reliability estimation for single dichotomous items based on Mokken's IRT model
Item reliability is of special interest for Mokken’s nonparametric item response theory, and is useful for the evaluation of item quality in nonparametric test construction research. It is also of interest for nonparametric person-fit analysis. Three methods for the estimation of the reliability of single dichotomous items are discussed. All methods are based on the assumptions of nondecreasing and nonintersecting item response functions. Based on analytical and monte carlo studies, it is concluded that one method is superior to the other two, because it has a smaller bias and a smaller sampling variance. This method also demonstrated some robustness under violation of the condition of nonintersecting item response functions. Index terms: item reliability, item response theory, Mokken model, nonparametric item response models, test construction
Selection of Alzheimer symptom items with manifest monotonicity and manifest invariant item ordering
Online Deliberation and the Public Sphere:Developing a Coding Manual to Assess Deliberation in Twitter Political Networks
Development and evaluation of a student-centered multimedia self-assessment instrument for social-communicative competence
Stream Productivity by Outermost Termination
Streams are infinite sequences over a given data type. A stream specification
is a set of equations intended to define a stream. A core property is
productivity: unfolding the equations produces the intended stream in the
limit. In this paper we show that productivity is equivalent to termination
with respect to the balanced outermost strategy of a TRS obtained by adding an
additional rule. For specifications not involving branching symbols
balancedness is obtained for free, by which tools for proving outermost
termination can be used to prove productivity fully automatically
Productivity of Stream Definitions
We give an algorithm for deciding productivity of a large and natural class of recursive stream definitions. A stream definition
is called ‘productive’ if it can be evaluated continuously in such a way that a uniquely determined stream is obtained as
the limit. Whereas productivity is undecidable for stream definitions in general, we show that it can be decided for ‘pure’
stream definitions. For every pure stream definition the process of its evaluation can be modelled by the dataflow of abstract
stream elements, called ‘pebbles’, in a finite ‘pebbleflow net(work)’. And the production of a pebbleflow net associated with
a pure stream definition, that is, the amount of pebbles the net is able to produce at its output port, can be calculated
by reducing nets to trivial nets
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