Three representations of the Ising model

Scientific Reports

Volumn 6, Issue , 2016, Pages

  Kruis, Joost ^a   Maris, Gunter ^a,b  

^a UNIVERSITY OF AMSTERDAM   (Netherlands)

^b Cito group   (Netherlands)

Author keywords

[No Author keywords available]

Indexed keywords

HUMAN; SCIENTIST; THEORETICAL MODEL;

EID: 84990942813     PISSN: None     EISSN: 20452322     Source Type: Journal    
DOI: 10.1038/srep34175     Document Type: Article

References (54)

1. Bandura, A. Social cognitive theory: An agentic perspective. Asian J. Soc. Psychol. 2, 21-41 (1999).
2. Costner, H. L. Theory, deduction, and rules of correspondence. Am. J. Sociol. 75, 245-263 (1969).
3. Edwards, J. R. & Bagozzi, R. P. On the nature and direction of relationships between constructs and measures. Psychol. Methods 5, 155-174 (2000).
4. Pearl, J. Causality: models, reasoning and inference. Economet. Theor. 19, 675-685 (2003).
5. Reichenbach, H. The Direction of Time (University of California Press, Berkeley, 1956).
6. Fornell, C. & Bookstein, F. L. Two structural equation models: Lisrel and PLS applied to consumer exit-voice theory. J. Mark. Res. 19, 440-452 (1982).
7. Markus, K. A. & Borsboom, D. Reflective measurement models, behavior domains, and common causes. New Ideas Psychol. 31, 54-64 (2013).
8. Spearman, C. General intelligence objectively determined and measured. Am. J. Psychol. 15, 201-293 (1904).
9. Jensen, A. R. The g factor: The science of mental ability (Praeger, Westport, 1998).
10. McCrae, R. R. & Costa, P. T. Empirical and theoretical status of the five-factor model of personality traits in The SAGE Handbook of Personality Theory and Assessment: Volume 1 - Personality Theories and Models 273-294 (SAGE, London, 2008).
11. Borsboom, D., Mellenbergh, G. J. & van Heerden, J. The concept of validity. Psychol. Rev. 111, 1061-1071 (2004).
12. Borsboom, D. Psychometric perspectives on diagnostic systems. J. Clin. Psychol. 64, 1089-1108 (2008).
13. Popper, K. R. The Logic of Scientific Discovery (Hutchinson, London, 1959).
14. Van Der Maas, H. L. et al. A dynamical model of general intelligence: the positive manifold of intelligence by mutualism. Psychol. Rev. 113, 842-861 (2006).
15. Epskamp, S., Maris, G., Waldorp, L. J. & Borsboom, D. Network Psychometrics in Handbook of Psychometrics. (Wiley, New York, 2015).
16. Lee, T.-D. & Yang, C.-N. Statistical theory of equations of state and phase transitions II. Lattice gas and Ising model. Phys. Rev. 87, 410-419 (1952).
17. Besag, J. Spatial interaction and the statistical analysis of lattice systems. J. R. Stat. Soc. Series B Stat. Methodol. (Methodological) 36, 192-236 (1974).
18. Besag, J. Statistical analysis of non-lattice data. Statistician 24, 179-195 (1975).
19. Barzel, B. & Barabasi, A. L. Universality in network dynamics. Nat. Phys. 9, 673-681 (2013).
20. Ising, E. Beitrag zur theorie des ferromagnetismus. Zeit. Phys. 31, 253-258 (1925).
21. Jaynes, E. T. Information theory and statistical mechanics. Phys. Rev. 106, 620-630 (1957).
22. Barabasi, A. L. The network takeover. Nat. Phys. 8, 14-16 (2012).
23. Cramer, A. O., Waldorp, L. J., van der Maas, H. L. & Borsboom, D. Comorbidity: A network perspective. Behav. Brain Sci. 33, 137-150 (2010).
24. Borsboom, D. & Cramer, A. O. Network analysis: an integrative approach to the structure of psychopathology. Annu. Rev. Clin. Psychol. 9, 91-121 (2013).
25. Schmittmann, V. D. et al. Deconstructing the construct: A network perspective on psychological phenomena. New Ideas Psychol. 31, 43-53 (2013).
26. van Borkulo, C. D. et al. A new method for constructing networks from binary data. Sci. Rep. 4, 5918 (2014).
27. Blalock, H. M. Causal models involving unmeasured variables in stimulus-response situations in Causal Models in the Social Sciences 335-347 (Aldine-Atherton, Chicago, 1971).
28. Bollen, K. & Lennox, R. Conventional wisdom on measurement: A structural equation perspective. Psychol. Bull. 110, 305-314 (1991).
29. Hauser, R. M. Disaggregating a social-psychological model of educational attainment. Soc. Sci. Res. 1, 159-188 (1972).
30. Greenland, S., Pearl, J. & Robins, J. M. Causal diagrams for epidemiologic research. Epidemiology 10, 37-48 (1999).
31. Heckman, J. J. Sample selection bias as a specification error. Econometrica 47, 153-161 (1979).
32. Greenland, S. Quantifying biases in causal models: classical confounding vs collider-stratification bias. Epidemiology 14, 300-306 (2003).
33. Hernan, M. A., Hernandez-Daz, S. & Robins, J. M. A structural approach to selection bias. Epidemiology 15, 615-625 (2004).
34. Elwert, F. & Winship, C. Endogenous selection bias: The problem of conditioning on a collider variable. Annu. Rev. Sociol. 40, 31-53 (2014).
35. Rasch, G. Probabilistic Models for some Intelligence and Attainment Tests (The Danish Institute of Educational Research, Copenhagen, 1960).
36. Christofides, N. Graph Theory: An Algorithmic Approach (New York: Academic Press Inc, 1975).
37. Kac, M. Statistical physics: Phase transitions and superfluidity in Brandeis University Summer Institute in Theoretical Physics, Vol. 1 (eds Chretien, M., Gross, E. & Deser, S.) 241-305 (Gordon and Breach Science Publishers, New York, 1968).
38. Stanley, H. E. Introduction to Phase Transitions and Critical Phenomena. (Oxford University Press, New York, 1971).
39. Ellis, R. S. & Newman, C. M. The statistics of curie-weiss models. J. Stat. Phys. 19, 149-161 (1978).
40. Olkin, I. & Tate, R. F. Multivariate correlation models with mixed discrete and continuous variables. Ann. Math. Stat. 32, 448-465 (1961).
41. Emch, G. G. & Knops, H. J. Pure thermodynamical phases as extremal kms states. J. Math. Phys. 11, 3008-3018 (1970).
42. Cox, D. R. & Wermuth, N. A note on the quadratic exponential binary distribution. Biometrika 81, 403-408 (1994).
43. McCullagh, P. Exponential mixtures and quadratic exponential families. Biometrika 81, 721-729 (1994).
44. Lauritzen, S. L. Graphical models (Oxford University Press, USA, 1996).
45. Anderson, C. J. & Yu, H.-T. Log-multiplicative association models as item response models. Psychometrika 72, 5-23 (2007).
46. Marsman, M., Maris, G., Bechger, T. & Glas, C. Bayesian inference for low-rank ising networks. Sci. Rep. 5, 9050 (2015).
47. Reckase, M. Multidimensional Item Response Theory (Springer, 2009).
48. Mellenbergh, G. J. Item bias and item response theory. Int. J. Educ. Res. 13, 127-143 (1989).
49. Meredith, W. Measurement invariance, factor analysis and factorial invariance. Psychometrika 58, 525-543 (1993).
50. Costa, P. T. & MacCrae, R. R. Revised NEO personality inventory (NEO PI-R) and NEO five-factor inventory (NEO FFI): Professional manual (Psychological Assessment Resources, 1992).
51. Goldberg, L. R. An alternative description of personality: the big-five factor structure. J. Pers. Soc. Psychol. 59, 1216-1229 (1990).
52. Barrick, M. R. & Mount, M. K. The big five personality dimensions and job performance: a meta-analysis. Pers. Psychol. 44, 1-26 (1991).
53. Beck, A. T., Ward, C. H., Mendelson, M., Mock, J. & Erbaugh, J. An inventory for measuring depression. Arch. Gen. Psychiatry 562, 53-63 (1961).
54. Beck, A. T., Steer, R. A. & Carbin, M. G. Psychometric properties of the beck depression inventory: Twenty-five years of evaluation. Clin. Psychol. Rev. 8, 77-100 (1988