Conditional symmetry model as a better alternative to Symmetry Model for rater agreement measure

In almost all life or social science researches, subjects are classified into categories by raters, interviewers or observers. Many approaches have been proposed by various authors for analyzing the data or the results obtained from these raters. Symmetry and conditional symmetry models are models designed for square tables like the one arising from the raters results. Conditional symmetry model which possessed an extra parameter for the off-diagonal cells is a special case to symmetry. In this research work, we examined the effect of the extra parameter introduced by conditional symmetry model over that of symmetry on structure of agreement as well as their fittings. Generalized linear model (GLM) approach was used to model the loglinear model forms of these models with empirical examples. We observed that conditional symmetry based on it extra parameter gave a tremendous improvement to the significant level of the test statistics over that of its symmetry model counterpart, hence conditional symmetry model is better for raters agreement modelling which require symmetric table

A review of agreement measure as a subset of association measure between raters

Agreement can be regarded as a special case of association and not the other way round. Virtually in all life or social science researches, subjects are being classified into categories by raters, interviewers or observers and both association and agreement measures can be obtained from the results of this researchers. The distinction between association and agreement for a given data is that, for two responses to be perfectly associated we require that we can predict the category of one response from the category of the other response, while for two response to agree, they must fall into the identical category. Which hence mean, once there is agreement between the two responses, association has already exist, however, strong association may exist between the two responses without any strong agreement. Many approaches have been proposed by various authors for measuring each of these measures. In this work, we present some up till date development on these measures statistics

Modelling Negative Binomial as a substitute model to Poisson for raters agreement on ordinal scales with sparse data

The Poisson distribution has been widely used for modelling rater agreement using loglinear models. Mostly in all life or social science researches, subjects are being classified into categories by rater, interviewers or observers and most of these tables indicate that the cell counts are mixtures of either too big values and two small values or zeroes which are sparse data. We refer to sparse as a situation when a large number of cell frequencies are very small. For these kinds of tables, there are tendencies for overdispersion in which the variance of the outcome or response exceeds the nominal variance, that is, when the response is greater than it should be under the given model or the true variance is bigger than the mean. In these types of situations assuming Poisson models means we are imposing the mean-variance equality restriction on the estimation. This implies that we will effectively be requiring the variance to be less than it really is, and also, as a result, we will underestimate the true variability in the data. Lastly, this will lead us to underestimating the standard errors, and so to overestimating the degree of precision in the coefficients. The Negative Binomial, which has a variance function, would be better for modelling rater agreement with sparse data in the table in order to allow the spread of the observations or counts. We observed that assuming Negative Binomial as the underline sampling plan is better for modelling rater agreement when there are sparse data in a limited number of example

Photoproduction of W Bosons at HERA: Reweighting Method for implementing QCD Corrections in Monte Carlo Programs

A procedure of implementing QCD corrections in Monte Carlo programs by a reweighting method is described for the photoproduction of W bosons at HERA. Tables for W boson production in LO and NLO are given in bins of the transverse momentum of the W boson and its rapidity.Comment: 39 pages, latex, 5 figure