BulletinofThe Japanese Classification Society

Volume 7
December 17, 1993
Tokyo, JAPANJCS Bulletin/ December 17, 1993

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ContentsAnalysis of Questionnaire Data by Combination of AHP and AID
Takao Ishizuka
Faculty of Business Administration, Asia University
Classification of Remotely Sensed Images Using Finite Mixture
Distribution Models
Nagatomo Nakamura The Graduate University for Advanced Studies
Sadanori Konishi and Noboru Ohsumi
The Institute of Statistical Mathematics
A Classification Method by Using the Rank Graph
Mariko Murata
The Graduate University for Advanced Studies
Yasumasa Baba
The Institute of Statistical Mathematics
Consideration on Examination Permitted to Bring Reference Materials
Keiji Yajima
Science University of Tokyo
Performance and Interpretation of AID, CART, MARS and ABLE
Hideaki Watanabe, Yoshihiro Matsubara and Masashi Goto
Shionogi Kaiseki Center
A Hierarchical Clustering Method based on Reducibility Property andReciprocal Nearest Neighbors
Miyuki Takahashi
Nihon University
Noboru Ohsumi
The Institute of Statistical Mathematics
Determining Core Journals in Social Sciences: Ranking Scholarly
Journals by the Number of Articles and Citations
Wang Jie, Kazuaki Kishida, and Sachiko Matsui
University of Library and Information Science
Evaluation of Root Resorption in Cleft Lips and Palate Patients
Underwent Orthodontic Treatment.
Sumimasa Ohtsuka, Kazunobu Imamura, Fumiya Ohmori, Yasuhiro Wada,
Yoshinobu Shibasaki Department of Orthodontics, Showa University Dental School
Noboru Ohsumi
The Institute of Statistical Mathematics

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Analysis of Questionnaire Data by Combination of AHP and AID
Takao Ishizuka
Faculty of Business Administration
Asia UniversityAbstract
The purpose of this paper is to propose a new method of questionnaire data analysis.
Considering convenient answering and subsequent data processing, multiple-item selectiontyped questions are often used.
However, it is sometimes difficult to select one corresponding item from multiple items in casethat the definitions of each item are inexplicit, or multiple items are fit for the answer. Sameproblems occur even if multiple answers are permitted. At data processing stage, single orcross statistical tables are computed. But, we obtain little information from those computer
outputs other than frequency distributions of each item.
We propose a combinatorial utilization of AHP and AID. AHP is a decision making method ofmultiple objective type proposed by T. Saarty (1981). By introducing AHP, a traditional
multiple-item selection typed questions can be changed to paired comparison between items
typed questions. The essence of AHP is the computation of eigenvalues of paired comparison
matrix. Paired comparison matrixes are similar to sociometry matrixes or similarity matrixes ofType 4 Quantification theory by T.Hayashi. As a result, we obtain not only the order of thedegree of importance between items but also quantitative weights of each items reflecting thedegree of importance. It is very important to stratify original sample data into homogeneousgroups for obtaining stable and reliable statistics.
In our study, AID (Morgan & Sonquist; 1963) is used for homogenization by using AHP
weight values as outer criterion and profiles or other questionnaire data as explanation variables.
The combinatorial method proposed in this paper can be decomposed into two stages. The firststage is the extraction of the principal component by AHP, and the second stage is the clusteringby AID.
We'd like to develop a integrated method from structured design of questionnaires to analysis ofquestionnaire data.
References[1]Saarty, T. L. (1981): The Analytic Hierarchy Process, McGraw-Hill[2]Morgan,J. N. & Sonquist, J. A.: J. Amer.Statist.Assoc.,58, pp.415-434.

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Classification of Remotely Sensed Images
Using Finite Mixture Distribution Models
Nagatomo Nakamura
The Graduate University for Advanced Studies
Sadanori Konishiand Noboru Ohsumi
The Institute of Statistical Mathematics

Abstract
This paper describes classification procedure using finite mixture model for LANDSAT image
data. The following problems arise in classification an image data:(1) At each pixel in an image a vector of observations is measured, and the distribution of thesemeasurements is approximated by a mixture model for which a pixel may contain some objects.
(2) In certain case the data sets have heavier-tailed distributions than the normal.
The objective of this paper is to examine a classification procedure using a multivariate normal
mixture model and a multivariate t mixture model, and to verify a validity of latter model. The
procedure estimates a rough segmentation of the objects for the purpose of exploring the featureof an overall image data. An estimation methodology using EM algorithm with re-weighting
methodfor multivariate t mixture model is proposed. Another objective is to develop the coloringprocedure that visualizes the characteristics as the result of a classification. Examples arepresented in order to show how these procedures work for real image data.

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A Classification Method by Using the Rank Graph
Mariko Murata
The Graduate University for Advanced Studies
Yasumasa Baba
The Institute of Statistical Mathematics

Abstract
In this paper, a method for classifing items and judges from ranked observations by using therank graph is proposed. The rank graph was proposed originally as a descriptive one in whichan average rank and a degree of concordance of ranks assigned toeach item are represented by
the vector called item vector.
As the distribution of an item vector is asymptotically approximated by a 2-dimensional normaldistribution, we can obtain an elliptic confidence region of the item vector. It will be shown that
it is possible to classify the items and the judges hierarchically according to the confidencecoefficient.
Keywords: ranked observation, graphical representation, rank graph, classification

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Consideration on Examination Permittedto Bring Reference Materials
Keiji Yajima
Science University of Tokyo

Abstract
The two kinds of examinations have been applied to students with regard to a subject of general
introduction to engineering. At the end of the first semester an examination permitted to bringreference materials including their note and books was carried out and in the following second
semester standard examination not capable to bring any reference material was put in which adesign to check the effect of remembrance provoked by the examination with references wasbuilt-in. Total number of applicants were 152 and all students who wrote correct answer in thefirst semester attained to a number of 98 and among them only a number of ten students got
right response to the same kind of question of second test regarding a specific term related withpatent system in Japan and US. The examination with references could not get high evaluation.
Finally correspondence analysis to the classified written words has been adopted to show thecharacteristics of two types of examinations.

JCS Bulletin/ December 17, 1993

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Hideaki Watanabe
Yoshihiro Matsubara
Masashi Goto
Shionogi Kaiseki Center
Abstract(not received)

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A Hierarchical Clustering Method
based onReducibility Property and Reciprocal Nearest Neighbors
Miyuki Takahashi
Nihon University
Noboru Ohsumi
The Institute of Statistical Mathematics

Abstract
Various procedures will be required in order to classify large data sets under a personal
computer environment and then observe the clustering process by graphical and coloredrepresentation. The objective of this paper is to propose some procedures for presenting theskeleton of the data structure, and not to directly display the distribution of large-scale data.
The clustering process for classifying large-scale data sets (exceeding 10,000 observations) andrepresenting the classification results smoothly with computer graphics is provided. The
clustering process proposed here is essentially summarized as follows:
Step 1: Preliminary classification
A partial data set is sampled from a given data set at random in a certain proportion.
Next, sampled data is subjected to the initial classification. At this time, the number ofclusters is specified to be as large as possible to generate a large number of groups. The
distance table is not used because it requires the use of a large matrix. The classification
thereby completed is displayed by tree representation as the "preliminary classification."
Step 2: Refinement by reclassification
All individuals in the data set subjected to the initial classification are classified
consecutively using the tree obtained in Step 3 as a decision tree (i.e., each individual isassigned consecutively to some cluster in the tree by a binary decision rule). After all
individuals are assigned, "reclassification" or "refinement" is conducted using thecentroid vector of each cluster at the terminal end of the tree. The reclassification
obtained in this step is the fine adjustment of the relationship between each cluster and theindividuals belonging to each cluster. At this time, the tree structure is reconstructedusing the RNN-rule (reciprocal nearest neighbor rule) and the NN-chains (nearestneighbor chains).
Step 3: Output presentation
The tree structure obtained by reclassification is displayed and observed again, and iscompared with that obtained by the preliminary classification.
In our talk, the experimental results obtained using artificial data sets were presented.

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Determining Core Journals in Social Sciences: Ranking ScholarlyJournals by the Number of Articles and Citations
Wang Jie
Kazuaki Kishida
Sachiko Matsui
University of Library and Information ScienceAbstract
The purpose of this study is to assess the importance of individual social science journals by
two indicators: the number of articles and the number of citations received. The first indicatorshows the extent to which the journal contributes to dissemination of research output in aparticular discipline. The list of journals ranked by this indicator, in general, shows thatnumerous articles are concentrated in a few 'core' journals. This regularity is often referred toas 'Bradford's law.' The second indicator--the number of citations received--represents thesignificance or impact of cited articles, and is employed to compensate for important journals
that publish only a small number of articles.
The core journal list by the number of articles (called "List A") was compiled from theInternational Bibliography of the Social Sciences (IBSS), which covers four disciplines-economics, political science, sociology and cultural anthropology--and maintains a high level ofselectivity of entries. Nearly 93,000 entries of journal articles in the IBSS (1981-1985) wereanalyzed, and the concentration of articles in a small number of journals was observed in all
four disciplines. The core journals were defined as the top group of journals in the ranking
containing one-third of the total articles in each discipline. In economics, for example, only 75journals (3.9% of all the economics journals in the IBSS) were identified as core journals. On
the other hand, the data on citations were obtained from the Journal Citation Report (JCR) of
the Social Science Citation Index (SSCI) that provides an 'impact factor', calculated as the ratio
between citations and citable articles published. The core journal list (called "List B") of the top
one-third journals was produced based on this indicator for each of the four disciplines.
A comparison between List A and List B in economics showed that only 20 journals appear inboth lists, out of 75 journals in List A and 55 journals in List B. This means that these 20journals are the most important journals according to both indicators. In addition, 55 journals
appearing only in List A and 35 journals in List B are important ones by the first or secondindicator. These core journal lists, including those for the other three disciplines, can be utilizedfor library collection management.

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Evaluation of Root Resorption in Cleft LipsandPalate Patients Underwent Orthodontic TreatmentSumimasa Ohtsuka
Kazunobu Imamura
Fumiya Ohmori
Yasuhiro WadaYoshinobu Shibasaki
Department of Orthodontics, Showa University Dental School
Noboru Ohsumi
The Institute of Statistical Mathematics

Abstract
Root resorption is one of the most troublesome problems in orthodontic treatment. To avoid
root resorption is a key to successful treatment. Orthodontic treatment of Cleft Lip andPalate(CLP) patients with severe malocclusions, such as collapsed , severe narrow maxillaryarch and crossbite is very difficult. Then, long term treatment period and a great deal of toothmovement is inevitable, which is thought to induce more root resorption.
The object of this study is to investigate the condition of the root resorption in CLP patients
who underwent orthodontic treatment.
Materials and methods
Cleft and Class III group as a control were selected from finished orthodontic treatment cases inthe department of orthodontics, Showa University. The Class III group showed reversed
occlusion, which could be thought same treatment mechanics used as the Cleft group. In thosecases periapical root was completed and root resorption had not been detected on pretreatment
radiographs. Examined teeth were upper four incisors. Evaluation of root resorption was donein degree and shape by oral X-ray films before and after orthodontic treatment. Besides, theamount of changes of upper central incisors were measured by both frontal and lateralcepharograms at before and after treatment.
Results
To compare with Cl. III patients, Cleft group showed more root resorption during orthodontictreatment. The shape of resorbed root in Cleft group was quite different from Cl. III group.
Most of Cleft group showed oblique resorbed pattern and most of Cl. III group were horizontal
patterns. In Cleft group the teeth near to the cleft side were higher frequency of root resorption
than the other side.
These results suggest that a new approach in orthodontic treatment of Cleft patients such as
surgical procedure should be required actively.
References[1] Goldson, L. and Henrikson, C.: Root resorption during Begg treatment: a longitudinalroengenographic study. Amer. J. Orthod., 68: 55-66, 1975.
[2] Malmgren, O. and Goldson, L. et al.: Root resorption after orthodontic treatment oftraumatized teeth. Amer. J. Orthod., 82: 487-491, 1982.

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