Department of Statistics Papers
Parent: Department of Statistics, UCLA
eScholarship stats: Breakdown by Item for November, 2024 through February, 2025
| Item | Title | Total requests | Download | View-only | %Dnld |
|---|---|---|---|---|---|
| 2mk8r49v | Comparative Fit Indices in Structural Models | 405 | 358 | 47 | 88.4% |
| 583610fv | A Generalized Definition of the Polychoric Correlation Coefficient | 346 | 49 | 297 | 14.2% |
| 7qp4604r | The Phi-coefficient, the Tetrachoric Correlation Coefficient, and the Pearson-Yule Debate | 307 | 58 | 249 | 18.9% |
| 87t603ns | On Statistical Criteria: Theory, History, and Applications | 288 | 8 | 280 | 2.8% |
| 53n4f34m | Bayesian networks | 274 | 26 | 248 | 9.5% |
| 6gv9n38c | Causal Diagrams for Empirical Research | 260 | 179 | 81 | 68.8% |
| 27s1d3h7 | Robust Statistical Modeling Using the t- Distribution | 233 | 136 | 97 | 58.4% |
| 6cn677bx | Comparative Fit Indices in Structural Models | 212 | 26 | 186 | 12.3% |
| 9q6553kr | Object Perception as Bayesian Inference | 179 | 146 | 33 | 81.6% |
| 24w7k7m1 | Mahalanobis' Distance Beyond Normal Distributions | 173 | 7 | 166 | 4.0% |
| 8cs5815x | Vision as Bayesian Inference: Analysis by Synthesis? | 173 | 59 | 114 | 34.1% |
| 3141h70c | Scaling Corrections for Statistics in Covariance Structure Analysis | 143 | 118 | 25 | 82.5% |
| 490131xj | The Causal Foundations of Structural Equation Modeling | 138 | 120 | 18 | 87.0% |
| 2bz9c0zr | Comparing Robust Properties of A, D, E and G-Optimal Designs | 125 | 7 | 118 | 5.6% |
| 45x689gq | Identifiability of Path-Specific Effects | 112 | 27 | 85 | 24.1% |
| 8940b4k8 | Approximating the Distribution of Pareto Sums | 107 | 71 | 36 | 66.4% |
| 9050x4r4 | Reproducible Research. The Bottom Line | 100 | 7 | 93 | 7.0% |
| 84j7c2w5 | Regression with Missing X's: A Review | 98 | 75 | 23 | 76.5% |
| 49m7794d | A Comparison of Some Methodologies for the Factor Analysis of Non-Normal Likert Variables: A Note on the Size of the Model | 94 | 81 | 13 | 86.2% |
| 65z429wc | Assessment and Propagation of Model Uncertainty | 94 | 17 | 77 | 18.1% |
| 4bp1t13z | Designing Studies for Dose Response | 90 | 5 | 85 | 5.6% |
| 3tv1b3bg | Transportability across studies: A formal approach | 88 | 19 | 69 | 21.6% |
| 5pk7v8c5 | What are Textons? | 77 | 9 | 68 | 11.7% |
| 0fd986xb | Information Theory and an Extension of the Maximum Likelihood Principle by Hirotogu Akaike | 76 | 55 | 21 | 72.4% |
| 9nh0d6wj | Probabilities of Causation: Three Counterfactual Interpretations and their Identification | 76 | 7 | 69 | 9.2% |
| 05n729v1 | Homogeneity Analysis in R: The Package homals | 75 | 11 | 64 | 14.7% |
| 3s62r0d6 | Simpson's Paradox: An Anatomy | 75 | 60 | 15 | 80.0% |
| 7wg0k7xq | Applications of Convex Analysis to Multidimensional Scaling | 74 | 35 | 39 | 47.3% |
| 7tn3p6jx | Causal Diagrams | 72 | 58 | 14 | 80.6% |
| 4q74x3fr | The Foundations of Causal Inference | 71 | 16 | 55 | 22.5% |
| 2hw5r3tm | Why There Is No Statistical Test for Confounding, Why Many Think There Is, and Why They Are Almost Right | 70 | 26 | 44 | 37.1% |
| 5qk1s0dv | Object Perception as Bayesian Inference | 70 | 60 | 10 | 85.7% |
| 2cs5m2sh | A Primer on Robust Regression | 69 | 42 | 27 | 60.9% |
| 6xc0172f | Isotone Optimization in R: Pool-Adjacent-Violators Algorithm (PAVA) and Active Set Methods | 69 | 54 | 15 | 78.3% |
| 13k6x1w8 | Jakob Bernoulli's Theory of Inference | 65 | 4 | 61 | 6.2% |
| 1gf0b3m7 | Simple and Canonical Correspondence Analysis Using the R Package anacor | 65 | 6 | 59 | 9.2% |
| 6cs342k2 | Myth, Confusion, and Science in Causal Analysis | 65 | 16 | 49 | 24.6% |
| 0zj8s368 | Statistical Assumptions as Empirical Commitments | 63 | 38 | 25 | 60.3% |
| 4x788631 | A Comparison of Maximum-Likelihood and Asymptotically Distribution-Free Methods of Treating Incomplete Non-Normal Data | 61 | 37 | 24 | 60.7% |
| 0789f7d3 | The Gifi System for Nonlinear Multivariate Analysis | 60 | 38 | 22 | 63.3% |
| 45h3t3t2 | Bias in Factor Score Regression and a Simple Solution | 60 | 0 | 60 | 0.0% |
| 4cg0k6g0 | Determination of Sample Size for Multilevel Model Design | 60 | 37 | 23 | 61.7% |
| 29w3z5b6 | Geometrical Aspects of Multiple Correspondence Analysis: Implications for the Coordinate Scaling Debate | 59 | 56 | 3 | 94.9% |
| 3mw1p0mb | Slicing Regression: Dimension Reduction via Inverse Regression | 58 | 50 | 8 | 86.2% |
| 9zx0h8k6 | Aspects of Graphical Models Connected with Causality | 58 | 45 | 13 | 77.6% |
| 3jq067x8 | Bounds on Treatment Effects from Studies with Imperfect Compliance | 56 | 20 | 36 | 35.7% |
| 7sw581hc | Sharp Quadratic Majorization in One Dimension | 54 | 1 | 53 | 1.9% |
| 059919k4 | An Introduction to Ensemble Methods for Data Analysis | 53 | 13 | 40 | 24.5% |
| 7pj7b53n | Converting Statistical Literacy Resources to Data Science Resources | 53 | 10 | 43 | 18.9% |
| 7mw1d7tq | Functional-Coefficient Regression Models for Nonlinear Time Series | 52 | 41 | 11 | 78.8% |
Note: Due to the evolving nature of web traffic, the data presented here should be considered approximate and subject to revision. Learn more.