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Contemporary issues in exploratory data mining in the behavioral sciences

Contemporary issues in exploratory data mining in the behavioral sciences (1회 대출)

자료유형
단행본
개인저자
McArdle, John J. Ritschard, Gilbert, 1950-.
서명 / 저자사항
Contemporary issues in exploratory data mining in the behavioral sciences / edited by John J. McArdle and Gilbert Ritschard.
발행사항
New York, NY :   Routledge,   2014.  
형태사항
xxi, 473 p. : ill. ; 23 cm.
총서사항
Quantitative methodology series
ISBN
9780415817066 (hardback : alk. paper) 9780415817097 (pbk. : alk. paper)
서지주기
Includes bibliographical references and index.
일반주제명
Social sciences --Statistical methods. Social sciences --Research --Data processing. Data mining --Social aspects.
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020 ▼a 9780415817066 (hardback : alk. paper)
020 ▼a 9780415817097 (pbk. : alk. paper)
035 ▼a (KERIS)REF000017062003
040 ▼a DLC ▼b eng ▼c DLC ▼e rda ▼d DLC ▼d 211009
050 0 0 ▼a HA29 ▼b .C746 2014
082 0 0 ▼a 006.3/12 ▼2 23
084 ▼a 006.312 ▼2 DDCK
090 ▼a 006.312 ▼b C761
245 0 0 ▼a Contemporary issues in exploratory data mining in the behavioral sciences / ▼c edited by John J. McArdle and Gilbert Ritschard.
260 ▼a New York, NY : ▼b Routledge, ▼c 2014.
300 ▼a xxi, 473 p. : ▼b ill. ; ▼c 23 cm.
490 1 ▼a Quantitative methodology series
504 ▼a Includes bibliographical references and index.
650 0 ▼a Social sciences ▼x Statistical methods.
650 0 ▼a Social sciences ▼x Research ▼x Data processing.
650 0 ▼a Data mining ▼x Social aspects.
700 1 ▼a McArdle, John J.
700 1 ▼a Ritschard, Gilbert, ▼d 1950-.
830 0 ▼a Quantitative methodology series.
945 ▼a KLPA

소장정보

No. 소장처 청구기호 등록번호 도서상태 반납예정일 예약 서비스
No. 1 소장처 중앙도서관/서고6층/ 청구기호 006.312 C761 등록번호 111735492 도서상태 대출가능 반납예정일 예약 서비스 B M

컨텐츠정보

목차

Part I: Methodological Aspects J.J. McArdle, Exploratory Data Mining Using Decision Trees in the Behavioral Sciences. G. Ritschard, CHAID and Earlier Supervised Tree Methods. J.Kopf, T. Augustin, C. Strobl, The potential of model-based recursive partitioning in the social sciences ?Revisiting Ockham's Razor. A.M. Brandmaier, Timo von Oertzen, J.J. McArdle, U. Lindenberger, Exploratory Data Mining with Structural Equation Model Trees. G. Ritschard, F. Losa, P.Origoni, Validating Tree Descriptions of Women’s Labor Participation with Deviance-based Criteria. G.A. Marcoulides, W.Leite, Exploratory Data Mining Algorithms for Conducting Searches in Structural Equation Modeling: A Comparison of Some Fit Criteria. K.J. Grimm, N. Ram, M. P. Shiyko, L. L. Lo, A Simulation Study of the Ability of Growth Mixture Models to Uncover Growth Heterogeneity. R. Piccarreta, C.H. Elzinga, Mining for Association between Life Course Domains. G.Ritschard, R. Burgin, M. Studer, Exploratory Mining of Life Event Histories. Part II: Applications C.A. Prescott, Clinical versus Statistical Prediction of Zygosity in Adult Twin Pairs: An Application of Classification Trees. J.J. McArdle, Dealing with Longitudinal Attrition Using Logistic Regression and Decision Tree Analyses. J.J. McArdle, Adaptive Testing of the Number Series Test Using Standard Approaches and a New Decision Tree Analysis Approach. T. S. Paskus, Using EDM to Identify Academic Risk among College Student-Athletes in the United States. S. B. Scott, B. R. Whitehead, C. S. Bergeman, and L. Pitzer, Understanding Global Perceptions of Stress in Adulthood through Tree-Based Exploratory Data Mining. P. Ghisletta, Recursive Partitioning to Study Terminal Decline in the Berlin Aging Study. Y. Zhou, K.M. Kadlec, J. J. McArdle, Predicting Mortality from Demographics and Specific Cognitive Abilities in the Hawaii Family Study of Cognition. K. F. Widaman, K.J. Grimm, Exploratory Analysis of Effects of Prenatal Risk Factors on Intelligence in Children of Mothers with Phenylketonuria.


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