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  • multidimensional scaling  (7)
  • Cluster Analysis  (2)
  • Multidimensional scaling  (2)
  • 18-hydroxy-11-deoxycorticosterone, 18,21-hydroxy-4-pregnene-3,20-dione  (1)
  • 1
    Electronic Resource
    Electronic Resource
    The relationship between plasma 18-hydroxy-11-deoxycorticosterone levels and production of hypertension in the rat
    Amsterdam : Elsevier
    Journal of Steroid Biochemistry 14 (1981), S. 989-995 
    Details
    ISSN: 0022-4731
    Keywords: (18-OH-DOC) ; (DOCA) ; 11-deoxy-corticosterone acetate, 21-hydroxy-4-pregnene-3,20-dione acetate ; 18-hydroxy-11-deoxycorticosterone, 18,21-hydroxy-4-pregnene-3,20-dione
    Source: Elsevier Journal Backfiles on ScienceDirect 1907 - 2002
    Topics: Biology , Chemistry and Pharmacology
    Type of Medium: Electronic Resource
    URL: http://linkinghub.elsevier.com/retrieve/pii/0022-4731(81)90206-5
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    Paper (German National Licenses)
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  • 2
    Electronic Resource
    Electronic Resource
    Fitting an extended INDSCAL model to three-way proximity data (1995)
    Springer
    Journal of classification 12 (1995), S. 57-71 
    Details
    ISSN: 1432-1343
    Keywords: Weighted Euclidean model ; INDSCAL ; Multidimensional scaling ; Specificities ; Monotone splines
    Source: Springer Online Journal Archives 1860-2000
    Topics: Mathematics
    Notes: Abstract The INDSCAL individual differences scaling model is extended by assuming dimensions specific to each stimulus or other object, as well as dimensions common to all stimuli or objects. An “alternating maximum likelihood” procedure is used to seek maximum likelihood estimates of all parameters of this EXSCAL (Extended INDSCAL) model, including parameters of monotone splines assumed in a “quasi-nonmetric” approach. The rationale for and numerical details of this approach are described and discussed, and the resulting EXSCAL method is illustrated on some data on perception of musical timbres.
    Type of Medium: Electronic Resource
    URL: http://dx.doi.org/10.1007/BF01202267
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    Paper (German National Licenses)
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  • 3
    Electronic Resource
    Electronic Resource
    An evaluation of five algorithms for generating an initial configuration for SINDSCAL (1989)
    Springer
    Journal of classification 6 (1989), S. 105-119 
    Details
    ISSN: 1432-1343
    Keywords: Individual differences ; Multidimensional scaling ; Rational starting configuration ; INDSCAL
    Source: Springer Online Journal Archives 1860-2000
    Topics: Mathematics
    Notes: Abstract Five different methods for obtaining a rational initial estimate of the stimulus space in the INDSCAL model were compared using the SINDSCAL program for fitting INDSCAL. The effect of the number of stimuli, the number of subjects, the dimensionality, and the amount of error on the quality and efficiency of the final SINDSCAL solution were investigated in a Monte Carlo study. We found that the quality of the final solution was not affected by the choice of the initialization method, suggesting that SINDSCAL finds a global optimum regardless of the initialization method used. The most efficient procedures were the methods proposed by by de Leeuw and Pruzansky (1978) and by Flury and Gautschi (1986) for the simultaneous diagonalization of several positive definite symmetric matrices, and a method based on linearly constraining the stimulus space using the CANDELINC approach developed by Carroll, Pruzansky, and Kruskal (1980).
    Type of Medium: Electronic Resource
    URL: http://dx.doi.org/10.1007/BF01908591
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    Paper (German National Licenses)
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  • 4
    Electronic Resource
    Electronic Resource
    A quasi-nonmetric method for multidimensional scaling VIA an extended euclidean model (1989)
    Springer
    Psychometrika 54 (1989), S. 217-229 
    Details
    ISSN: 1860-0980
    Keywords: multidimensional scaling ; monotone spline ; specific dimensions ; maximum likelihood estimation
    Source: Springer Online Journal Archives 1860-2000
    Topics: Psychology
    Notes: Abstract An Extended Two-Way Euclidean Multidimensional Scaling (MDS) model which assumes both common and specific dimensions is described and contrasted with the “standard” (Two-Way) MDS model. In this Extended Two-Way Euclidean model then stimuli (or other objects) are assumed to be characterized by coordinates onR common dimensions. In addition each stimulus is assumed to have a dimension (or dimensions) specific to it alone. The overall distance between objecti and objectj then is defined as the square root of the ordinary squared Euclidean distance plus terms denoting the specificity of each object. The specificity,s j , can be thought of as the sum of squares of coordinates on those dimensions specific to objecti, all of which have nonzero coordinatesonly for objecti. (In practice, we may think of there being just one such specific dimension for each object, as this situation is mathematically indistinguishable from the case in which there are more than one.) We further assume that δ ij =F(d ij ) +e ij where δ ij is the proximity value (e.g., similarity or dissimilarity) of objectsi andj,d ij is the extended Euclidean distance defined above, whilee ij is an error term assumed i.i.d.N(0, σ2).F is assumed either a linear function (in the metric case) or a monotone spline of specified form (in the quasi-nonmetric case). A numerical procedure alternating a modified Newton-Raphson algorithm with an algorithm for fitting an optimal monotone spline (or linear function) is used to secure maximum likelihood estimates of the paramstatistics) can be used to test hypotheses about the number of common dimensions, and/or the existence of specific (in addition toR common) dimensions. This approach is illustrated with applications to both artificial data and real data on judged similarity of nations.
    Type of Medium: Electronic Resource
    URL: http://dx.doi.org/10.1007/BF02294516
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    Paper (German National Licenses)
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  • 5
    Electronic Resource
    Electronic Resource
    Candelinc: A general approach to multidimensional analysis of many-way arrays with linear constraints on parameters (1980)
    Springer
    Psychometrika 45 (1980), S. 3-24 
    Details
    ISSN: 1860-0980
    Keywords: constrained least-squares ; multilinear models ; bilinear models ; INDSCAL ; multidimensional scaling ; 3-mode factor analysis ; CANDECOMP ; LINCINDS ; multivariate analysis
    Source: Springer Online Journal Archives 1860-2000
    Topics: Psychology
    Notes: Abstract Very general multilinear models, called CANDELINC, and a practical least-squares fitting procedure, also called CANDELINC, are described for data consisting of a many-way array. The models incorporate the possibility of general linear constraints, which turn out to have substantial practical value in some applications, by permitting better prediction and understanding. Description of the model, and proof of a theorem which greatly simplifies the least-squares fitting process, is given first for the case involving two-way data and a bilinear model. Model and proof are then extended to the case ofN-way data and anN-linear model for generalN. The caseN = 3 covers many significant applications. Two applications are described: one of two-way CANDELINC, and the other of CANDELINC used as a constrained version of INDSCAL. Possible additional applications are discussed.
    Type of Medium: Electronic Resource
    URL: http://dx.doi.org/10.1007/BF02293596
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    Paper (German National Licenses)
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  • 6
    Electronic Resource
    Electronic Resource
    Spatial versus tree representations of proximity data (1982)
    Springer
    Psychometrika 47 (1982), S. 3-24 
    Details
    ISSN: 1860-0980
    Keywords: multidimensional scaling ; clustering ; tree structures ; additive trees
    Source: Springer Online Journal Archives 1860-2000
    Topics: Psychology
    Notes: Abstract In this paper we investigated two of the most common representations of proximities, two-dimensional euclidean planes and additive trees. Our purpose was to develop guidelines for comparing these representations, and to discover properties that could help diagnose which representation is more appropriate for a given set of data. In a simulation study, artificial data generated either by a plane or by a tree were scaled using procedures for fitting either a plane (KYST) or a tree (ADDTREE). As expected, the appropriate model fit the data better than the inappropriate model for all noise levels. Furthermore, the two models were roughly comparable: for all noise levels, KYST accounted for plane data about as well as ADDTREE accounted for tree data. Two properties of the data proved useful in distinguishing between the models: the skewness of the distribution of distances, and the proportion of elongated triangles, which measures departures from the ultrametric inequality, Applications of KYST and ADDTREE to some twenty sets of real data, collected by other investigators, showed that most of these data could be classified clearly as favoring either a tree or a two-dimensional representation.
    Type of Medium: Electronic Resource
    URL: http://dx.doi.org/10.1007/BF02293848
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    Paper (German National Licenses)
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  • 7
    Electronic Resource
    Electronic Resource
    Synthesized clustering: A method for amalgamating alternative clustering bases with differential weighting of variables (1984)
    Springer
    Psychometrika 49 (1984), S. 57-78 
    Details
    ISSN: 1860-0980
    Keywords: Cluster Analysis ; Variable Importance
    Source: Springer Online Journal Archives 1860-2000
    Topics: Psychology
    Notes: Abstract In the application of clustering methods to real world data sets, two problems frequently arise: (a) how can the various contributory variables in a specific battery be weighted so as to enhance some cluster structure that may be present, and (b) how can various alternative batteries be combined to produce a single clustering that “best” incorporates each contributory set. A new method is proposed (SYNCLUS, SYNthesizedCLUStering) for dealing with these two problems.
    Type of Medium: Electronic Resource
    URL: http://dx.doi.org/10.1007/BF02294206
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    Paper (German National Licenses)
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  • 8
    Electronic Resource
    Electronic Resource
    The estimation of ultrametric and path length trees from rectangular proximity data (1984)
    Springer
    Psychometrika 49 (1984), S. 289-310 
    Details
    ISSN: 1860-0980
    Keywords: Cluster Analysis ; Trees
    Source: Springer Online Journal Archives 1860-2000
    Topics: Psychology
    Notes: Abstract A least-squares algorithm for fitting ultrametric and path length or additive trees to two-way, two-mode proximity data is presented. The algorithm utilizes a penalty function to enforce the ultrametric inequality generalized for asymmetric, and generally rectangular (rather than square) proximity matrices in estimating an ultrametric tree. This stage is used in an alternating least-squares fashion with closed-form formulas for estimating path length constants for deriving path length trees. The algorithm is evaluated via two Monte Carlo studies. Examples of fitting ultrametric and path length trees are presented.
    Type of Medium: Electronic Resource
    URL: http://dx.doi.org/10.1007/BF02306021
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    Paper (German National Licenses)
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  • 9
    Electronic Resource
    Electronic Resource
    Confidence regions for INDSCAL using the jackknife and bootstrap techniques (1984)
    Springer
    Psychometrika 49 (1984), S. 475-491 
    Details
    ISSN: 1860-0980
    Keywords: Individual differences ; multidimensional scaling ; stability ; standard errors ; pseudovalues ; maximum likelihood ; resampling schemes
    Source: Springer Online Journal Archives 1860-2000
    Topics: Psychology
    Notes: Abstract Bootstrap and jackknife techniques are used to estimate ellipsoidal confidence regions of group stimulus points derived from INDSCAL. The validity of these estimates is assessed through Monte Carlo analysis. Asymptotic estimates of confidence regions based on a MULTISCALE solution are also evaluated. Our findings suggest that the bootstrap and jackknife techniques may be used to provide statements regarding the accuracy of the relative locations of points in space. Our findings also suggest that MULTISCALE asymptotic estimates of confidence regions based on small samples provide an optimistic view of the actual statistical reliability of the solution.
    Type of Medium: Electronic Resource
    URL: http://dx.doi.org/10.1007/BF02302586
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    Paper (German National Licenses)
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  • 10
    Electronic Resource
    Electronic Resource
    Three-way metric unfolding via alternating weighted least squares (1985)
    Springer
    Psychometrika 50 (1985), S. 275-300 
    Details
    ISSN: 1860-0980
    Keywords: multidimensional scaling ; unfolding ; preference analysis
    Source: Springer Online Journal Archives 1860-2000
    Topics: Psychology
    Notes: Abstract Three-way unfolding was developed by DeSarbo (1978) and reported in DeSarbo and Carroll (1980, 1981) as a new model to accommodate the analysis of two-mode three-way data (e.g., nonsymmetric proximities for stimulus objects collected over time) and three-mode, three-way data (e.g., subjects rendering preference judgments for various stimuli in different usage occasions or situations). This paper presents a revised objective function and new algorithm which attempt to prevent the common type of degenerate solutions encountered in typical unfolding analysis. We begin with an introduction of the problem and a review of three-way unfolding. The three-way unfolding model, weighted objective function, and new algorithm are presented. Monte Carlo work via a fractional factorial experimental design is described investigating the effect of several data and model factors on overall algorithm performance. Finally, three applications of the methodology are reported illustrating the flexibility and robustness of the procedure.
    Type of Medium: Electronic Resource
    URL: http://dx.doi.org/10.1007/BF02294106
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