Detecting response styles by using dual scaling of successive categories

A response style denotes a certain mapping of latent preferences toa rating scale that is common among a certain group of individuals.For example, individuals from the same country may assign highratings to the majority of objects regardless of the specificpreferences for the objects. The existence of response styles causesproblems in international and cross-cultural research as it makes ithard to compare findings. Moreover, even within homogeneous samples,response styles make it difficult to expose the underlyingpreference structure. Detecting the existence and influence of aresponse style is typically a difficult issue as the underlyingpreferences are not directly observable. Hence, we can never be sureif the observed ratings are the result of a response style or anadequate representation of the preferences. In this paper, weconsider the use of dual scaling as a tool to detect the existenceof a response style. By means of a simulation study, we assess theperformance of the proposed method.

Multidimensional scaling

Multidimensional scaling is a statistical technique to visualize dissimilarity data. In multidimensional scaling, objects are represented as points in a usually two dimensional space, such that the distances between the points match the observed dissimilarities as closely as possible. Here, we discuss what kind of data can be used for multidimensional scaling, what the essence of the technique is, how to choose the dimensionality, transformations of the dissimilarities, and some pitfalls to watch out for when using multidimensional scaling.

Generalized canonical correlation analysis with missing values

Two new methods for dealing with missing values in generalized canonicalcorrelation analysis are introduced. The first approach, which does notrequire iterations, is a generalization of the Test Equating method availablefor principal component analysis. In the second approach, missing values areimputed in such a way that the generalized canonical correlation analysisobjective function does not increase in subsequent steps. Convergence isachieved when the value of the objective function remains constant. By meansof a simulation study, we assess the performance of the new methods. Wecompare the results with those of two available methods; the missing-datapassive method, introduced Gifi's homogeneity analysis framework, and theGENCOM algorithm developed by Green and Carroll.generalized canoncial correlation analysis;missing values

Differential effects of colleges on the labour market success of their graduates

This paper explores the effects of colleges for higher vocational education on the labour market success of their graduates. Using data about the labour market position of Dutch graduates from higher vocational education, and applying multi-level statistical modelling techniques it is shown that for four domains (finding a job, level of job, monthly wages, and wages per hour) the colleges did hardly differ substantially. Most of the institutional variation occured at the department level within the colleges, but these department effects appeared to be small as well and not always very stable over the years. The discussion focuses on the implication for using labour market data for the construction of institutional performance indicators. It is shown that the ranking of colleges on their labour market performance changes as soon as input variables are controlled for. It is therefore important to look at the ‘net'' outcomes or ‘added value'' rather than the ‘gross'' outcomes.labour market entry;

Seriation by constrained correspondence analysis: a simulation study

One of the many areas in which Correspondence Analysis (CA) is an effectivemethod, concerns ordination problems. For example, CA is a well-knowntechnique for the seriation of archaeological assemblages. A problem withthe CA seriation solution, however, is that only a relative ordering of theassemblages is obtained. To improve the usual CA solution, a constrained CAapproach that incorporates additional information in the form of equalityand inequality constraints concerning the time points of the assemblages maybe considered. Using such constraints, explicit dates can be assigned to theseriation solution. In this paper, we extend the set of constraints that canbe used in CA by introducing interval constraints. That is, constraints thatput the CA\\ solution within a specific time-frame. Moreover, we study thequality of the constrained CA solution in a simulation study. In particular,by means of the simulation study we are able to assess how well ordinary andconstrained CA can recover the true time order. Furthermore, for theconstrained approach, we see how well the true dates are retrieved. Thesimulation study is set up in such a way that it mimics the data of a seriesof ceramic assemblages consisting of the locally produced tableware fromSagalassos (SW Turkey). We find that the dating of the assemblages on thebasis of constraints appears to work quite well.

Area Biplots

Classical multivariate analysis techniques such as principal components analysis and correspondence analysis use inner products to estimate data values. The results of these techniques may be visualized by representing the row and column points jointly in a biplot where the projection of a row point onto a column point vector followed by a multiplication by the length of the column point vector gives the inner-product that estimates the corresponding data element. In this paper, we propose a newvisualization: after a 90 degrees rotation of the row points, the areas spanned by a triangle of a row point, a column point and the origin estimate the data values. In contrast to the projection biplot, the areas spanned by different row and column points can be compared directly. Areas can only be produced for two dimensions at a time, but higher dimensional solutions can be represented by summing areas over subsequent pairs of dimensions. Here, the area biplot is developed for principal components analysis, correspondence analysis, and for interaction biplots but has general applicability.interaction;correspondence analysis;visualization;principal component analysis;biplot

Which skills protect graduates against a slack labour market?

This paper explores the relationship between graduates’ skill levels and the risk of overeducationand unemployment in 17 European countries. We distinguish between field-specific and generalskills and between two labour market segments, the occupational domain of a particular field ofstudy and the labour market segment which requires general skills. In line with the predictions ofthe crowding out hypothesis, we find that the level of protection afforded by field-specificskills against the risk of overeducation increases with the degree of excess labour supply in theoccupational domain of the graduate’s field of study. Conversely, general skills offer moreprotection against the risk of overeducation when excess labour supply in the labour marketsegment which requires general skills is higher. Field-specific skills also protect graduatesagainst the risk of unemployment, whereas graduates’ level of general skills appears to beunrelated to the risk of becoming unemployed.labour market entry;