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Contemporary issues in exploratory data mining in the behavioral sciences

Contemporary issues in exploratory data mining in the behavioral sciences (Loan 1 times)

Material type
단행본
Personal Author
McArdle, John J. Ritschard, Gilbert, 1950-.
Title Statement
Contemporary issues in exploratory data mining in the behavioral sciences / edited by John J. McArdle and Gilbert Ritschard.
Publication, Distribution, etc
New York, NY :   Routledge,   2014.  
Physical Medium
xxi, 473 p. : ill. ; 23 cm.
Series Statement
Quantitative methodology series
ISBN
9780415817066 (hardback : alk. paper) 9780415817097 (pbk. : alk. paper)
Bibliography, Etc. Note
Includes bibliographical references and index.
Subject Added Entry-Topical Term
Social sciences --Statistical methods. Social sciences --Research --Data processing. Data mining --Social aspects.
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005 20150429124226
008 150428s2014 nyua b 001 0 eng d
010 ▼a 2013006082
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

Holdings Information

No. Location Call Number Accession No. Availability Due Date Make a Reservation Service
No. 1 Location Main Library/Western Books/ Call Number 006.312 C761 Accession No. 111735492 Availability Available Due Date Make a Reservation Service B M

Contents information

Table of Contents

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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