메뉴 건너뛰기




Volumn 18, Issue 1, 2013, Pages 71-86

Structural equation model trees

Author keywords

Exploratory data mining; Model based trees; Recursive partitioning; Structural equation modeling

Indexed keywords

ARTICLE; HUMAN; STATISTICAL ANALYSIS; STATISTICAL MODEL; STATISTICS; WECHSLER INTELLIGENCE SCALE;

EID: 84883009529     PISSN: 1082989X     EISSN: None     Source Type: Journal    
DOI: 10.1037/a0030001     Document Type: Article
Times cited : (130)

References (81)
  • 2
    • 33846022821 scopus 로고    scopus 로고
    • Lifespan theory in developmental psychology
    • W. Damon & R. Lerner (Eds.), New York, NY: Wiley.
    • Baltes, P., Lindenberger, U., & Staudinger, U. (2006). Lifespan theory in developmental psychology. In W. Damon & R. Lerner (Eds.), Handbook of child psychology (Vol. 1, pp. 569-664). New York, NY: Wiley.
    • (2006) Handbook of child psychology , vol.1 , pp. 569-664
    • Baltes, P.1    Lindenberger, U.2    Staudinger, U.3
  • 3
    • 31944452324 scopus 로고    scopus 로고
    • An introduction to ensemble methods for data analysis
    • doi:10.1177/0049124105283119
    • Berk, R. (2006). An introduction to ensemble methods for data analysis. Sociological Methods & Research, 34, 263-295. doi:10.1177/0049124105283119
    • (2006) Sociological Methods & Research , vol.34 , pp. 263-295
    • Berk, R.1
  • 4
    • 33846516584 scopus 로고    scopus 로고
    • Pattern recognition and machine learning
    • New York, NY: Springer.
    • Bishop, C. (2006). Pattern recognition and machine learning (Vol. 4). New York, NY: Springer.
    • (2006) , vol.4
    • Bishop, C.1
  • 5
    • 0347249769 scopus 로고    scopus 로고
    • An algorithm for the hierarchical organization of path diagrams and calculation of components of expected covariance
    • doi:10.1207/S15328007SEM0902_2
    • Boker, S., McArdle, J., & Neale, M. (2002). An algorithm for the hierarchical organization of path diagrams and calculation of components of expected covariance. Structural Equation Modeling: A Multidisciplinary Journal, 9, 174-194. doi:10.1207/S15328007SEM0902_2
    • (2002) Structural Equation Modeling: A Multidisciplinary Journal , vol.9 , pp. 174-194
    • Boker, S.1    Mcardle, J.2    Neale, M.3
  • 6
    • 84856970800 scopus 로고    scopus 로고
    • OpenMx: Multipurpose software for statistical modeling [Computer software manual]
    • Retrieved from
    • Boker, S., Neale, M., Maes, H., Wilde, M., Spiegel, M., Brick, T. R.,... Fox, J. (2010). OpenMx: Multipurpose software for statistical modeling [Computer software manual]. Retrieved from http://openmx.psyc.virginia.edu
    • (2010)
    • Boker, S.1    Neale, M.2    Maes, H.3    Wilde, M.4    Spiegel, M.5    Brick, T.R.6    Fox, J.7
  • 7
    • 32744460393 scopus 로고    scopus 로고
    • Latent differential equation modeling with multivariate multi-occasion indicators
    • In K. van Montfort, J. Oud, & A. Satorra (Eds.), Dordrecht, the Netherlands: Kluwer Academic.
    • Boker, S., Neale, M., & Rausch, J. (2004). Latent differential equation modeling with multivariate multi-occasion indicators. In K. van Montfort, J. Oud, & A. Satorra (Eds.), Recent developments on structural equation models: Theory and applications (pp. 151-174). Dordrecht, the Netherlands: Kluwer Academic.
    • (2004) Recent developments on structural equation models: Theory and applications , pp. 151-174
    • Boker, S.1    Neale, M.2    Rausch, J.3
  • 8
    • 0003556833 scopus 로고
    • Structural equations with latent variables
    • Oxford, England: Wiley.
    • Bollen, K. (1989). Structural equations with latent variables. Oxford, England: Wiley.
    • (1989)
    • Bollen, K.1
  • 9
    • 84883002823 scopus 로고    scopus 로고
    • semtree: Recursive partitioning of structural equation models in R [Computer software manual]
    • Available from
    • Brandmaier, A. M. (2012). semtree: Recursive partitioning of structural equation models in R [Computer software manual]. Available from http://www.brandmaier.de/semtree
    • (2012)
    • Brandmaier, A.M.1
  • 10
    • 0035478854 scopus 로고    scopus 로고
    • Random forests
    • doi: 10.1023/A:1010933404324
    • Breiman, L. (2001). Random forests. Machine Learning, 45, 5-32. doi: 10.1023/A:1010933404324
    • (2001) Machine Learning , vol.45 , pp. 5-32
    • Breiman, L.1
  • 11
    • 0003802343 scopus 로고
    • Classification and regression trees
    • Belmont, CA: Wadsworth International.
    • Breiman, L., Friedman, J. H., Olshen, R. A., & Stone, C. J. (1984). Classification and regression trees. Belmont, CA: Wadsworth International.
    • (1984)
    • Breiman, L.1    Friedman, J.H.2    Olshen, R.A.3    Stone, C..4
  • 12
    • 0001963735 scopus 로고
    • Generalized least squares estimators in the analysis of covariance structures
    • Browne, M. (1974). Generalized least squares estimators in the analysis of covariance structures. South African Statistical Journal, 8, 1-24.
    • (1974) South African Statistical Journal , vol.8 , pp. 1-24
    • Browne, M.1
  • 13
    • 84965455705 scopus 로고
    • Alternative ways of assessing model fit
    • doi:10.1177/0049124192021002005
    • Browne, M., & Cudeck, R. (1992). Alternative ways of assessing model fit. Sociological Methods Research, 21, 230-258. doi:10.1177/0049124192021002005
    • (1992) Sociological Methods Research , vol.21 , pp. 230-258
    • Browne, M.1    Cudeck, R.2
  • 14
    • 11244354640 scopus 로고    scopus 로고
    • LOTUS: An algorithm for building accurate and comprehensible logistic regression trees
    • doi:10.1198/106186004X13064
    • Chan, K., & Loh, W. (2004). LOTUS: An algorithm for building accurate and comprehensible logistic regression trees. Journal of Computational and Graphical Statistics, 13, 826-852. doi:10.1198/106186004X13064
    • (2004) Journal of Computational and Graphical Statistics , vol.13 , pp. 826-852
    • Chan, K.1    Loh, W.2
  • 16
    • 18444397785 scopus 로고    scopus 로고
    • A note on normal theory power calculation in SEM with data missing completely at random
    • doi:10.1207/s15328007sem1202_4
    • Dolan, C., van der Sluis, S., & Grasman, R. (2005). A note on normal theory power calculation in SEM with data missing completely at random. Structural Equation Modeling: A Multidisciplinary Journal, 12, 245-262. doi:10.1207/s15328007sem1202_4
    • (2005) Structural Equation Modeling: A Multidisciplinary Journal , vol.12 , pp. 245-262
    • Dolan, C.1    van der Sluis, S.2    Grasman, R.3
  • 17
    • 0035756118 scopus 로고    scopus 로고
    • The impact of nonnormality on full information maximum-likelihood estimation for structural equation models with missing data
    • doi:10.1037/1082-989X.6.4.352
    • Enders, C. K. (2001). The impact of nonnormality on full information maximum-likelihood estimation for structural equation models with missing data. Psychological Methods, 6, 352-370. doi:10.1037/1082-989X.6.4.352
    • (2001) Psychological Methods , vol.6 , pp. 352-370
    • Enders, C.K.1
  • 19
    • 0007170948 scopus 로고    scopus 로고
    • Canonical correlation analysis and structural equation modeling: What do they have in common
    • doi:10.1080/10705519709540060
    • Fan, X. (1997). Canonical correlation analysis and structural equation modeling: What do they have in common? Structural Equation Modeling: A Multidisciplinary Journal, 4, 65-79. doi:10.1080/10705519709540060
    • (1997) Structural Equation Modeling: A Multidisciplinary Journal , vol.4 , pp. 65-79
    • Fan, X.1
  • 20
    • 18444408338 scopus 로고    scopus 로고
    • Power of latent growth modeling for detecting group differences in linear growth trajectory parameters
    • doi:10.1207/S15328007SEM1003_3
    • Fan, X. (2003). Power of latent growth modeling for detecting group differences in linear growth trajectory parameters. Structural Equation Modeling: A Multidisciplinary Journal, 10, 380-400. doi:10.1207/S15328007SEM1003_3
    • (2003) Structural Equation Modeling: A Multidisciplinary Journal , vol.10 , pp. 380-400
    • Fan, X.1
  • 21
    • 0030285403 scopus 로고    scopus 로고
    • The KDD process for extracting useful knowledge from volumes of data
    • doi:10.1145/240455.240464
    • Fayyad, U. M., Piatetsky-Shapiro, G., & Smyth, P. (1996). The KDD process for extracting useful knowledge from volumes of data. Communications of the ACM, 39, 27-34. doi:10.1145/240455.240464
    • (1996) Communications of the ACM , vol.39 , pp. 27-34
    • Fayyad, U.M.1    Piatetsky-shapiro, G.2    Smyth, P.3
  • 22
    • 3042767455 scopus 로고    scopus 로고
    • Modeling latent growth curves with incomplete data using different types of structural equation modeling and multilevel software
    • doi:10.1207/s15328007sem1103_8
    • Ferrer, E., Hamagami, F., & McArdle, J. (2004). Modeling latent growth curves with incomplete data using different types of structural equation modeling and multilevel software. Structural Equation Modeling: A Multidisciplinary Journal, 11, 452-483. doi:10.1207/s15328007sem1103_8
    • (2004) Structural Equation Modeling: A Multidisciplinary Journal , vol.11 , pp. 452-483
    • Ferrer, E.1    Hamagami, F.2    Mcardle, J.3
  • 23
    • 0001581342 scopus 로고
    • Estimation for the multiple factor model when data are missing
    • doi:10.1007/BF02296204
    • Finkbeiner, C. (1979). Estimation for the multiple factor model when data are missing. Psychometrika, 44, 409-420. doi:10.1007/BF02296204
    • (1979) Psychometrika , vol.44 , pp. 409-420
    • Finkbeiner, C.1
  • 25
    • 30644456701 scopus 로고    scopus 로고
    • An abductive theory of scientific method
    • doi:10.1037/1082-989X.10.4.371
    • Haig, B. D. (2005). An abductive theory of scientific method. Psychological Methods, 10, 371-388. doi:10.1037/1082-989X.10.4.371
    • (2005) Psychological Methods , vol.10 , pp. 371-388
    • Haig, B.D.1
  • 26
    • 0035600240 scopus 로고    scopus 로고
    • Effect size, power, and sample size determination for structured means modeling and mimic approaches to between-groups hypothesis testing of means on a single latent construct
    • doi:10.1007/BF02294440
    • Hancock, G. (2001). Effect size, power, and sample size determination for structured means modeling and mimic approaches to between-groups hypothesis testing of means on a single latent construct. Psychometrika, 66, 373-388. doi:10.1007/BF02294440
    • (2001) Psychometrika , vol.66 , pp. 373-388
    • Hancock, G.1
  • 27
    • 0003684449 scopus 로고    scopus 로고
    • The elements of statistical learning
    • New York, NY: Springer.
    • Hastie, T., Tibshirani, R., & Friedman, J. (2001). The elements of statistical learning. New York, NY: Springer.
    • (2001)
    • Hastie, T.1    Tibshirani, R.2    Friedman, J.3
  • 29
    • 0026481045 scopus 로고
    • A practical and theoretical guide to measurement invariance in aging research
    • doi:10.1080/03610739208253916
    • Horn, J. L., & McArdle, J. J. (1992). A practical and theoretical guide to measurement invariance in aging research. Experimental Aging Research, 18, 117-144. doi:10.1080/03610739208253916
    • (1992) Experimental Aging Research , vol.18 , pp. 117-144
    • Horn, J.L.1    Mcardle, J.J.2
  • 32
    • 0033907286 scopus 로고    scopus 로고
    • Multiple comparisons in induction algorithms
    • doi:10.1023/A: 1007631014630
    • Jensen, D., & Cohen, P. (2000). Multiple comparisons in induction algorithms. Machine Learning, 38, 309-338. doi:10.1023/A: 1007631014630
    • (2000) Machine Learning , vol.38 , pp. 309-338
    • Jensen, D.1    Cohen, P.2
  • 33
    • 34250481868 scopus 로고
    • A general approach to confirmatory maximum likelihood factor analysis
    • doi:10.1007/BF02289343
    • Jöreskog, K. G. (1969). A general approach to confirmatory maximum likelihood factor analysis. Psychometrika, 34, 183-202. doi:10.1007/BF02289343
    • (1969) Psychometrika , vol.34 , pp. 183-202
    • Jöreskog, K.G.1
  • 34
    • 85004878812 scopus 로고
    • Estimation and testing of simplex models
    • doi: 10.1111/j.2044-8317.1970.tb00439.x
    • Jöreskog, K. G. (1970). Estimation and testing of simplex models. British Journal of Mathematical and Statistical Psychology, 23, 121-145. doi: 10.1111/j.2044-8317.1970.tb00439.x
    • (1970) British Journal of Mathematical and Statistical Psychology , vol.23 , pp. 121-145
    • Jöreskog, K.G.1
  • 35
    • 0003418565 scopus 로고    scopus 로고
    • LISREL 8 user's reference guide [Computer software manual]
    • Milwaukee, WI: Scientific Software.
    • Jöreskog, K. G., & Sörbom, D. (1996). LISREL 8 user's reference guide [Computer software manual]. Milwaukee, WI: Scientific Software.
    • (1996)
    • Jöreskog, K.G.1    Sörbom, D.2
  • 37
    • 0040089710 scopus 로고
    • A study of the power associated with testing factor mean differences under violations of factorial invariance
    • doi:10.1080/10705519509539999
    • Kaplan, D., & George, R. (1995). A study of the power associated with testing factor mean differences under violations of factorial invariance. Structural Equation Modeling: A Multidisciplinary Journal, 2, 101-118. doi:10.1080/10705519509539999
    • (1995) Structural Equation Modeling: A Multidisciplinary Journal , vol.2 , pp. 101-118
    • Kaplan, D.1    George, R.2
  • 38
    • 1542573450 scopus 로고    scopus 로고
    • Classification trees with unbiased multiway splits
    • doi:10.1198/016214501753168271
    • Kim, H., & Loh, W. (2001). Classification trees with unbiased multiway splits. Journal of the American Statistical Association, 96, 589-604. doi:10.1198/016214501753168271
    • (2001) Journal of the American Statistical Association , vol.96 , pp. 589-604
    • Kim, H.1    Loh, W.2
  • 39
    • 85164392958 scopus 로고
    • A study of cross-validation and bootstrap for accuracy estimation and model selection
    • In C. Mellish (Ed.), Los Altos, CA: Morgan Kaufmann.
    • Kohavi, R. (1995). A study of cross-validation and bootstrap for accuracy estimation and model selection. In C. Mellish (Ed.), International Joint Conference on Artificial Intelligence (Vol. 14, pp. 1137-1145). Los Altos, CA: Morgan Kaufmann.
    • (1995) International Joint Conference on Artificial Intelligence , vol.14 , pp. 1137-1145
    • Kohavi, R.1
  • 40
    • 38049035375 scopus 로고    scopus 로고
    • Practical experiences on the necessity of external validation
    • doi:10.1002/sim.3069
    • König, I. R., Malley, J. D., Weimar, C., Diener, H.-C., & Ziegler, A. (2007). Practical experiences on the necessity of external validation. Statistics in Medicine, 26, 5499-5511. doi:10.1002/sim.3069
    • (2007) Statistics in Medicine , vol.26 , pp. 5499-5511
    • König, I.R.1    Malley, J.D.2    Weimar, C.3    Diener, H.-C.4    Ziegler, A.5
  • 41
    • 0033807696 scopus 로고    scopus 로고
    • Adult age differences in task switching
    • doi:10.1037/0882-7974.15.1.126
    • Kray, J., & Lindenberger, U. (2000). Adult age differences in task switching. Psychology and Aging, 15, 126-147. doi:10.1037/0882-7974.15.1.126
    • (2000) Psychology and Aging , vol.15 , pp. 126-147
    • Kray, J.1    Lindenberger, U.2
  • 42
    • 67649135107 scopus 로고    scopus 로고
    • Circular analysis in systems neuroscience: The dangers of double dipping
    • doi:10.1038/nn.2303
    • Kriegeskorte, N., Simmons, W., Bellgowan, P., & Baker, C. (2009). Circular analysis in systems neuroscience: The dangers of double dipping. Nature Neuroscience, 12, 535-540. doi:10.1038/nn.2303
    • (2009) Nature Neuroscience , vol.12 , pp. 535-540
    • Kriegeskorte, N.1    Simmons, W.2    Bellgowan, P.3    Baker, C.4
  • 43
    • 84920841704 scopus 로고    scopus 로고
    • Structural equation modeling: A Bayesian approach
    • New York, NY: Wiley. doi:10.1002/9780470024737
    • Lee, S. (2007). Structural equation modeling: A Bayesian approach. New York, NY: Wiley. doi:10.1002/9780470024737
    • (2007)
    • Lee, S.1
  • 44
    • 0033409958 scopus 로고    scopus 로고
    • On selecting indicators for multivariate measurement and modeling with latent variables: When "good" indicators are bad and "bad" indicators are good
    • doi:10.1037/1082-989X.4.2.192
    • Little, T., Lindenberger, U., & Nesselroade, J. (1999). On selecting indicators for multivariate measurement and modeling with latent variables: When "good" indicators are bad and "bad" indicators are good. Psychological Methods, 4, 192-211. doi:10.1037/1082-989X.4.2.192
    • (1999) Psychological Methods , vol.4 , pp. 192-211
    • Little, T.1    Lindenberger, U.2    Nesselroade, J.3
  • 45
    • 0036556537 scopus 로고    scopus 로고
    • Regression trees with unbiased variable selection and interaction detection
    • Loh, W. (2002). Regression trees with unbiased variable selection and interaction detection. Statistica Sinica, 12, 361-386.
    • (2002) Statistica Sinica , vol.12 , pp. 361-386
    • Loh, W.1
  • 46
    • 0031312210 scopus 로고    scopus 로고
    • Split selection methods for classification trees
    • Loh, W., & Shih, Y. (1997). Split selection methods for classification trees. Statistica Sinica, 7, 815-840.
    • (1997) Statistica Sinica , vol.7 , pp. 815-840
    • Loh, W.1    Shih, Y.2
  • 47
    • 0033413980 scopus 로고    scopus 로고
    • Sample size in factor analysis
    • doi:10.1037/1082-989X.4.1.84
    • MacCallum, R., Widaman, K., Zhang, S., & Hong, S. (1999). Sample size in factor analysis. Psychological Methods, 4, 84-99. doi:10.1037/1082-989X.4.1.84
    • (1999) Psychological Methods , vol.4 , pp. 84-99
    • Maccallum, R.1    Widaman, K.2    Zhang, S.3    Hong, S.4
  • 48
    • 84864693069 scopus 로고    scopus 로고
    • Some ethical issues in factor analysis
    • In A. Panter & S. Sterber (Eds.), Washington, DC: American Psychological Association Press.
    • McArdle, J. J. (2010). Some ethical issues in factor analysis. In A. Panter & S. Sterber (Eds.), Quantitative methodology viewed through an ethical lens (pp. 313-339). Washington, DC: American Psychological Association Press.
    • (2010) Quantitative methodology viewed through an ethical lens , pp. 313-339
    • Mcardle, J.J.1
  • 49
    • 0347249768 scopus 로고
    • RAMpath: A computer program for automatic path diagrams
    • Hillsdale, NJ: Erlbaum.
    • McArdle, J. J., & Boker, S. M. (1990). RAMpath: A computer program for automatic path diagrams. Hillsdale, NJ: Erlbaum.
    • (1990)
    • Mcardle, J.J.1    Boker, S.M.2
  • 50
    • 0023285136 scopus 로고
    • Latent growth curves within developmental structural equation models
    • doi:10.2307/1130295
    • McArdle, J. J., & Epstein, D. (1987). Latent growth curves within developmental structural equation models. Child Development, 58, 110-133. doi:10.2307/1130295
    • (1987) Child Development , vol.58 , pp. 110-133
    • Mcardle, J.J.1    Epstein, D.2
  • 51
    • 0011832302 scopus 로고    scopus 로고
    • Latent difference score structural models for linear dynamic analyses with incomplete longitudinal data
    • In L. M. Collins & A. G. Sayer (Eds.), doi:10.1037/10409-005
    • McArdle, J. J., & Hamagami, F. (2001). Latent difference score structural models for linear dynamic analyses with incomplete longitudinal data. In L. M. Collins & A. G. Sayer (Eds.), New methods for the analysis of change (pp. 139-175). doi:10.1037/10409-005
    • (2001) New methods for the analysis of change , pp. 139-175
    • Mcardle, J.J.1    Hamagami, F.2
  • 52
    • 85004805728 scopus 로고
    • Some algebraic properties of the reticular action model for moment structures
    • doi:10.1111/j.2044-8317.1984.tb00802.x
    • McArdle, J. J., & McDonald, R. P. (1984). Some algebraic properties of the reticular action model for moment structures. British Journal of Mathematical and Statistical Psychology, 37, 234-251. doi:10.1111/j.2044-8317.1984.tb00802.x
    • (1984) British Journal of Mathematical and Statistical Psychology , vol.37 , pp. 234-251
    • Mcardle, J.J.1    Mcdonald, R.P.2
  • 53
    • 0026467003 scopus 로고
    • Age-based construct validation using structural equation modeling
    • doi:10.1080/03610739208253915
    • McArdle, J. J., & Prescott, C. A. (1992). Age-based construct validation using structural equation modeling. Experimental Aging Research, 18, 87-115. doi:10.1080/03610739208253915
    • (1992) Experimental Aging Research , vol.18 , pp. 87-115
    • Mcardle, J.J.1    Prescott, C.A.2
  • 54
    • 0004066260 scopus 로고    scopus 로고
    • Finite mixture models
    • New York, NY: Wiley.
    • McLachlan, G., & Peel, D. (2000). Finite mixture models. New York, NY: Wiley.
    • (2000)
    • Mclachlan, G.1    Peel, D.2
  • 55
    • 34250928365 scopus 로고
    • Notes on factorial invariance
    • doi:10.1007/BF02289699
    • Meredith, W. (1964). Notes on factorial invariance. Psychometrika, 29, 177-185. doi:10.1007/BF02289699
    • (1964) Psychometrika , vol.29 , pp. 177-185
    • Meredith, W.1
  • 56
    • 34147110831 scopus 로고
    • Measurement invariance, factor analysis and factorial invariance
    • doi:10.1007/BF02294825
    • Meredith, W. (1993). Measurement invariance, factor analysis and factorial invariance. Psychometrika, 58, 525-543. doi:10.1007/BF02294825
    • (1993) Psychometrika , vol.58 , pp. 525-543
    • Meredith, W.1
  • 57
    • 84882996982 scopus 로고    scopus 로고
    • Generalized measurement invariance tests with application to factor analysis (Working Paper No. 2011-09)
    • April, Retrieved from
    • Merkle, E. C., & Zeileis, A. (2011, April). Generalized measurement invariance tests with application to factor analysis (Working Paper No. 2011-09). Retrieved from http://EconPapers. RePEc.org/RePEc:inn:wpaper:2011-09
    • (2011)
    • Merkle, E.C.1    Zeileis, A.2
  • 58
    • 0000963321 scopus 로고    scopus 로고
    • General longitudinal modeling of individual differences in experimental designs: A latent variable framework for analysis and power estimation
    • doi:10.1037/1082-989X.2.4.371
    • Muthén, B., & Curran, P. (1997). General longitudinal modeling of individual differences in experimental designs: A latent variable framework for analysis and power estimation. Psychological Methods, 2, 371-402. doi:10.1037/1082-989X.2.4.371
    • (1997) Psychological Methods , vol.2 , pp. 371-402
    • Muthén, B.1    Curran, P.2
  • 59
    • 33744584654 scopus 로고
    • Induction of decision trees
    • doi:10.1007/BF00116251
    • Quinlan, J. (1986). Induction of decision trees. Machine Learning, 1, 81-106. doi:10.1007/BF00116251
    • (1986) Machine Learning , vol.1 , pp. 81-106
    • Quinlan, J.1
  • 60
    • 0023417432 scopus 로고
    • Simplifying decision trees
    • doi:10.1016/S0020-7373(87) 80053-6
    • Quinlan, J. (1987). Simplifying decision trees. International Journal of Man-Machine Studies, 27, 221-234. doi:10.1016/S0020-7373(87) 80053-6
    • (1987) International Journal of Man-Machine Studies , vol.27 , pp. 221-234
    • Quinlan, J.1
  • 61
    • 0003500248 scopus 로고
    • C4.5: Programs for machine learning
    • San Francisco, CA: Morgan Kaufmann.
    • Quinlan, J. (1993). C4.5: Programs for machine learning. San Francisco, CA: Morgan Kaufmann.
    • (1993)
    • Quinlan, J.1
  • 62
    • 84872289042 scopus 로고    scopus 로고
    • PATHMOX approach: Segmentation trees in partial least squares path modeling (Unpublished doctoral dissertation)
    • Universitat Politecnica de Catalunya, Catalonia, Spain.
    • Sanchez, G. (2009). PATHMOX approach: Segmentation trees in partial least squares path modeling (Unpublished doctoral dissertation). Universitat Politecnica de Catalunya, Catalonia, Spain.
    • (2009)
    • Sanchez, G.1
  • 63
    • 84882992589 scopus 로고    scopus 로고
    • pathmox: Segmentation trees in partial least squares path modeling (R package Version 0.1-1) [Computer software manual]
    • Available from
    • Sanchez, G., & Aluja, T. (2012). pathmox: Segmentation trees in partial least squares path modeling (R package Version 0.1-1) [Computer software manual]. Available from http://CRAN.R-project.org/package=pathmox
    • (2012)
    • Sanchez, G.1    Aluja, T.2
  • 64
    • 0000644048 scopus 로고
    • Tree-structured methods for longitudinal data
    • doi:10.1080/01621459.1992.10475220
    • Segal, M. (1992). Tree-structured methods for longitudinal data. Journal of the American Statistical Association, 87, 407-418. doi:10.1080/01621459.1992.10475220
    • (1992) Journal of the American Statistical Association , vol.87 , pp. 407-418
    • Segal, M.1
  • 65
    • 1842630388 scopus 로고    scopus 로고
    • A note on split selection bias in classification trees
    • doi:10.1016/S0167-9473(03)00064-1
    • Shih, Y. (2004). A note on split selection bias in classification trees. Computational Statistics and Data Analysis, 45, 457-466. doi:10.1016/S0167-9473(03)00064-1
    • (2004) Computational Statistics and Data Analysis , vol.45 , pp. 457-466
    • Shih, Y.1
  • 66
    • 0010930398 scopus 로고
    • The detection of interaction effects: A report on a computer program for the selection of optimal combinations of explanatory variables (No. 35)
    • Ann Arbor: University of Michigan, Institute for Social Research, Survey Research Center.
    • Sonquist, J., & Morgan, J. (1964). The detection of interaction effects: A report on a computer program for the selection of optimal combinations of explanatory variables (No. 35). Ann Arbor: University of Michigan, Institute for Social Research, Survey Research Center.
    • (1964)
    • Sonquist, J.1    Morgan, J.2
  • 67
    • 0000600340 scopus 로고
    • "General intelligence," objectively determined and measured
    • doi: 10.2307/1412107
    • Spearman, C. (1904). "General intelligence," objectively determined and measured. The American Journal of Psychology, 15, 201-293. doi: 10.2307/1412107
    • (1904) The American Journal of Psychology , vol.15 , pp. 201-293
    • Spearman, C.1
  • 68
    • 33847096395 scopus 로고    scopus 로고
    • Bias in random forest variable importance measures: Illustrations, sources and a solution
    • doi:10.1186/1471-2105-8-25
    • Strobl, C., Boulesteix, A., Zeileis, A., & Hothorn, T. (2007). Bias in random forest variable importance measures: Illustrations, sources and a solution. BMC Bioinformatics, 8, 25. doi:10.1186/1471-2105-8-25
    • (2007) BMC Bioinformatics , vol.8 , pp. 25
    • Strobl, C.1    Boulesteix, A.2    Zeileis, A.3    Hothorn, T.4
  • 69
    • 72449170109 scopus 로고    scopus 로고
    • An introduction to recursive partitioning: Rationale, application, and characteristics of classification and regression trees, bagging, and random forests
    • doi:10.1037/a0016973
    • Strobl, C., Malley, J., & Tutz, G. (2009). An introduction to recursive partitioning: Rationale, application, and characteristics of classification and regression trees, bagging, and random forests. Psychological Methods, 14, 323-348. doi:10.1037/a0016973
    • (2009) Psychological Methods , vol.14 , pp. 323-348
    • Strobl, C.1    Malley, J.2    Tutz, G.3
  • 70
    • 79955052335 scopus 로고    scopus 로고
    • Accounting for individual differences in Bradley-Terry models by means of recursive partitioning
    • Strobl, C., Wickelmaier, F., & Zeileis, A. (2011). Accounting for individual differences in Bradley-Terry models by means of recursive partitioning. Journal of Educational and Behavioral Statistics, 36, 135-153.
    • (2011) Journal of Educational and Behavioral Statistics , vol.36 , pp. 135-153
    • Strobl, C.1    Wickelmaier, F.2    Zeileis, A.3
  • 72
    • 0000142125 scopus 로고
    • "How big is big enough?" Sample size and goodness of fit in structural equation models with latent variables
    • doi:10.2307/1130296
    • Tanaka, J. (1987). "How big is big enough?" Sample size and goodness of fit in structural equation models with latent variables. Child Development, 58, 134-146. doi:10.2307/1130296
    • (1987) Child Development , vol.58 , pp. 134-146
    • Tanaka, J.1
  • 73
    • 77952740641 scopus 로고    scopus 로고
    • Simulating statistical power in latent growth curve modeling: A strategy for evaluating age-based changes in cognitive resources
    • In M. Crocker & J. Siekmann (Eds.), Heidelberg, Germany: Springer.
    • von Oertzen, T., Ghisletta, P., & Lindenberger, U. (2009). Simulating statistical power in latent growth curve modeling: A strategy for evaluating age-based changes in cognitive resources. In M. Crocker & J. Siekmann (Eds.), Resource-adaptive cognitive processes (pp. 95-117). Heidelberg, Germany: Springer.
    • (2009) Resource-adaptive cognitive processes , pp. 95-117
    • Von Oertzen, T.1    Ghisletta, P.2    Lindenberger, U.3
  • 74
    • 0003664194 scopus 로고
    • Wechsler Intelligence Scale for Children: Manual
    • New York, NY: Psychological Corporation.
    • Wechsler, D. (1949). Wechsler Intelligence Scale for Children: Manual. New York, NY: Psychological Corporation.
    • (1949)
    • Wechsler, D.1
  • 75
    • 0003441705 scopus 로고
    • Wechsler Adult Intelligence Scale-Revised
    • San Antonio, TX: Psychological Corporation.
    • Wechsler, D. (1981). Wechsler Adult Intelligence Scale-Revised. San Antonio, TX: Psychological Corporation.
    • (1981)
    • Wechsler, D.1
  • 76
    • 0001972601 scopus 로고
    • The large-sample distribution of the likelihood ratio for testing composite hypotheses
    • Wilks, S. S. (1938). The large-sample distribution of the likelihood ratio for testing composite hypotheses. Annals of Mathematical Statistics, 9, 60-62.
    • (1938) Annals of Mathematical Statistics , vol.9 , pp. 60-62
    • Wilks, S.S.1
  • 77
    • 0001445915 scopus 로고
    • The method of path coefficients
    • doi:10.1214/aoms/1177732676
    • Wright, S. (1934). The method of path coefficients. Annals of Mathematical Statistics, 5, 161-215. doi:10.1214/aoms/1177732676
    • (1934) Annals of Mathematical Statistics , vol.5 , pp. 161-215
    • Wright, S.1
  • 78
    • 84882987098 scopus 로고    scopus 로고
    • Evaluating model-based trees in practice (Tech. Rep. No. 32)
    • Vienna, Austria: Vienna University of Economics and Business, Department of Statistics and Mathematics.
    • Zeileis, A., Hothorn, T., & Hornik, K. (2006). Evaluating model-based trees in practice (Tech. Rep. No. 32). Vienna, Austria: Vienna University of Economics and Business, Department of Statistics and Mathematics.
    • (2006)
    • Zeileis, A.1    Hothorn, T.2    Hornik, K.3
  • 80
    • 0141931984 scopus 로고    scopus 로고
    • strucchange: An R package for testing for structural change in linear regression models
    • Zeileis, A., Leisch, F., Hornik, K., & Kleiber, C. (2002). strucchange: An R package for testing for structural change in linear regression models. Journal of Statistical Software, 7, 1-38.
    • (2002) Journal of Statistical Software , vol.7 , pp. 1-38
    • Zeileis, A.1    Leisch, F.2    Hornik, K.3    Kleiber, C.4
  • 81
    • 0003537282 scopus 로고    scopus 로고
    • Recursive partitioning in the health sciences
    • New York, NY: Springer-Verlag.
    • Zhang, H., & Singer, B. (1999). Recursive partitioning in the health sciences. New York, NY: Springer-Verlag.
    • (1999)
    • Zhang, H.1    Singer, B.2


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.