Department of Statistics Papers
Parent: Department of Statistics, UCLA
eScholarship stats: Breakdown by Item for September through December, 2024
Item | Title | Total requests | Download | View-only | %Dnld |
---|---|---|---|---|---|
2mk8r49v | Comparative Fit Indices in Structural Models | 469 | 405 | 64 | 86.4% |
583610fv | A Generalized Definition of the Polychoric Correlation Coefficient | 374 | 45 | 329 | 12.0% |
7qp4604r | The Phi-coefficient, the Tetrachoric Correlation Coefficient, and the Pearson-Yule Debate | 301 | 60 | 241 | 19.9% |
87t603ns | On Statistical Criteria: Theory, History, and Applications | 298 | 6 | 292 | 2.0% |
53n4f34m | Bayesian networks | 279 | 15 | 264 | 5.4% |
6gv9n38c | Causal Diagrams for Empirical Research | 247 | 176 | 71 | 71.3% |
27s1d3h7 | Robust Statistical Modeling Using the t- Distribution | 221 | 129 | 92 | 58.4% |
9q6553kr | Object Perception as Bayesian Inference | 219 | 186 | 33 | 84.9% |
8cs5815x | Vision as Bayesian Inference: Analysis by Synthesis? | 218 | 79 | 139 | 36.2% |
6cn677bx | Comparative Fit Indices in Structural Models | 190 | 7 | 183 | 3.7% |
24w7k7m1 | Mahalanobis' Distance Beyond Normal Distributions | 168 | 3 | 165 | 1.8% |
4bp1t13z | Designing Studies for Dose Response | 129 | 3 | 126 | 2.3% |
490131xj | The Causal Foundations of Structural Equation Modeling | 128 | 106 | 22 | 82.8% |
45x689gq | Identifiability of Path-Specific Effects | 124 | 27 | 97 | 21.8% |
3141h70c | Scaling Corrections for Statistics in Covariance Structure Analysis | 121 | 99 | 22 | 81.8% |
49m7794d | A Comparison of Some Methodologies for the Factor Analysis of Non-Normal Likert Variables: A Note on the Size of the Model | 104 | 90 | 14 | 86.5% |
65z429wc | Assessment and Propagation of Model Uncertainty | 93 | 20 | 73 | 21.5% |
7j01t5sf | On the Relation Between the Polychoric Correlation Coefficient and Spearman's Rank Correlation Coefficient | 86 | 10 | 76 | 11.6% |
8940b4k8 | Approximating the Distribution of Pareto Sums | 85 | 62 | 23 | 72.9% |
13k6x1w8 | Jakob Bernoulli's Theory of Inference | 82 | 3 | 79 | 3.7% |
2cs5m2sh | A Primer on Robust Regression | 78 | 54 | 24 | 69.2% |
0fd986xb | Information Theory and an Extension of the Maximum Likelihood Principle by Hirotogu Akaike | 77 | 55 | 22 | 71.4% |
2hw5r3tm | Why There Is No Statistical Test for Confounding, Why Many Think There Is, and Why They Are Almost Right | 77 | 22 | 55 | 28.6% |
4q74x3fr | The Foundations of Causal Inference | 77 | 12 | 65 | 15.6% |
9nh0d6wj | Probabilities of Causation: Three Counterfactual Interpretations and their Identification | 74 | 3 | 71 | 4.1% |
4x788631 | A Comparison of Maximum-Likelihood and Asymptotically Distribution-Free Methods of Treating Incomplete Non-Normal Data | 73 | 48 | 25 | 65.8% |
05n729v1 | Homogeneity Analysis in R: The Package homals | 72 | 7 | 65 | 9.7% |
0zj8s368 | Statistical Assumptions as Empirical Commitments | 72 | 52 | 20 | 72.2% |
29w3z5b6 | Geometrical Aspects of Multiple Correspondence Analysis: Implications for the Coordinate Scaling Debate | 72 | 65 | 7 | 90.3% |
6xc0172f | Isotone Optimization in R: Pool-Adjacent-Violators Algorithm (PAVA) and Active Set Methods | 72 | 61 | 11 | 84.7% |
0789f7d3 | The Gifi System for Nonlinear Multivariate Analysis | 71 | 58 | 13 | 81.7% |
3s62r0d6 | Simpson's Paradox: An Anatomy | 71 | 60 | 11 | 84.5% |
7786134t | Statistics and the Modern Student | 71 | 52 | 19 | 73.2% |
9zx0h8k6 | Aspects of Graphical Models Connected with Causality | 71 | 53 | 18 | 74.6% |
7wg0k7xq | Applications of Convex Analysis to Multidimensional Scaling | 68 | 38 | 30 | 55.9% |
84j7c2w5 | Regression with Missing X's: A Review | 68 | 55 | 13 | 80.9% |
7sw581hc | Sharp Quadratic Majorization in One Dimension | 67 | 1 | 66 | 1.5% |
1gf0b3m7 | Simple and Canonical Correspondence Analysis Using the R Package anacor | 66 | 4 | 62 | 6.1% |
3jq067x8 | Bounds on Treatment Effects from Studies with Imperfect Compliance | 64 | 23 | 41 | 35.9% |
8j29393d | Variable Selection via Penalized Likelihood | 62 | 35 | 27 | 56.5% |
3mw1p0mb | Slicing Regression: Dimension Reduction via Inverse Regression | 61 | 54 | 7 | 88.5% |
5pk7v8c5 | What are Textons? | 60 | 3 | 57 | 5.0% |
5qk1s0dv | Object Perception as Bayesian Inference | 60 | 51 | 9 | 85.0% |
3tv1b3bg | Transportability across studies: A formal approach | 59 | 13 | 46 | 22.0% |
2bz9c0zr | Comparing Robust Properties of A, D, E and G-Optimal Designs | 58 | 6 | 52 | 10.3% |
8gh5613r | Simpson's Paradox: An Anatomy | 58 | 16 | 42 | 27.6% |
7tn3p6jx | Causal Diagrams | 57 | 51 | 6 | 89.5% |
45h3t3t2 | Bias in Factor Score Regression and a Simple Solution | 54 | 1 | 53 | 1.9% |
9050x4r4 | Reproducible Research. The Bottom Line | 53 | 6 | 47 | 11.3% |
06h5156t | Statistical Software - Overview | 52 | 2 | 50 | 3.8% |
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