Department of Statistics, UCLA
Parent: UCLA
eScholarship stats: Breakdown by Item for August through November, 2024
| Item | Title | Total requests | Download | View-only | %Dnld |
|---|---|---|---|---|---|
| 2rj412j3 | Mate with the two Bishops in Kriegspiel | 953 | 945 | 8 | 99.2% |
| 2mk8r49v | Comparative Fit Indices in Structural Models | 487 | 419 | 68 | 86.0% |
| 583610fv | A Generalized Definition of the Polychoric Correlation Coefficient | 400 | 50 | 350 | 12.5% |
| 3sr461nd | Fixed and Random Effects in Panel Data Using Structural Equations Models | 377 | 30 | 347 | 8.0% |
| 7qp4604r | The Phi-coefficient, the Tetrachoric Correlation Coefficient, and the Pearson-Yule Debate | 315 | 70 | 245 | 22.2% |
| 87t603ns | On Statistical Criteria: Theory, History, and Applications | 305 | 14 | 291 | 4.6% |
| 53n4f34m | Bayesian networks | 281 | 18 | 263 | 6.4% |
| 6gv9n38c | Causal Diagrams for Empirical Research | 275 | 187 | 88 | 68.0% |
| 0pg6471b | Making sense of sensitivity: extending omitted variable bias | 258 | 146 | 112 | 56.6% |
| 27s1d3h7 | Robust Statistical Modeling Using the t- Distribution | 218 | 108 | 110 | 49.5% |
| 8cs5815x | Vision as Bayesian Inference: Analysis by Synthesis? | 217 | 83 | 134 | 38.2% |
| 9q6553kr | Object Perception as Bayesian Inference | 217 | 185 | 32 | 85.3% |
| 24w7k7m1 | Mahalanobis' Distance Beyond Normal Distributions | 189 | 8 | 181 | 4.2% |
| 6cn677bx | Comparative Fit Indices in Structural Models | 176 | 6 | 170 | 3.4% |
| 4bp1t13z | Designing Studies for Dose Response | 158 | 11 | 147 | 7.0% |
| 490131xj | The Causal Foundations of Structural Equation Modeling | 132 | 112 | 20 | 84.8% |
| 3141h70c | Scaling Corrections for Statistics in Covariance Structure Analysis | 125 | 98 | 27 | 78.4% |
| 45x689gq | Identifiability of Path-Specific Effects | 125 | 25 | 100 | 20.0% |
| 6gr648np | Benchmarking Computational Doublet-Detection Methods for Single-Cell RNA Sequencing Data | 125 | 7 | 118 | 5.6% |
| 7j01t5sf | On the Relation Between the Polychoric Correlation Coefficient and Spearman's Rank Correlation Coefficient | 120 | 20 | 100 | 16.7% |
| 0tg4t8bd | Recent Developments in Causal Inference and Machine Learning | 117 | 95 | 22 | 81.2% |
| 65z429wc | Assessment and Propagation of Model Uncertainty | 112 | 32 | 80 | 28.6% |
| 0789f7d3 | The Gifi System for Nonlinear Multivariate Analysis | 106 | 95 | 11 | 89.6% |
| 49m7794d | A Comparison of Some Methodologies for the Factor Analysis of Non-Normal Likert Variables: A Note on the Size of the Model | 106 | 85 | 21 | 80.2% |
| 2cs5m2sh | A Primer on Robust Regression | 96 | 69 | 27 | 71.9% |
| 8t51b39q | Emergent constraints on the large scale atmospheric circulation and regional hydroclimate: do they still work in CMIP6 and how much can they actually constrain the future? | 96 | 23 | 73 | 24.0% |
| 99b2s80w | Heider vs Simmel: Emergent Features in Dynamic Structures | 96 | 19 | 77 | 19.8% |
| 5h9374jn | Tool for tracking all-cause mortality and estimating excess mortality to support the COVID-19 pandemic response: All-cause mortality calculator for COVID-19 response | 95 | 9 | 86 | 9.5% |
| 0fd986xb | Information Theory and an Extension of the Maximum Likelihood Principle by Hirotogu Akaike | 94 | 67 | 27 | 71.3% |
| 3mw1p0mb | Slicing Regression: Dimension Reduction via Inverse Regression | 91 | 82 | 9 | 90.1% |
| 9nh0d6wj | Probabilities of Causation: Three Counterfactual Interpretations and their Identification | 91 | 14 | 77 | 15.4% |
| 80s9k72v | An accurate and robust imputation method scImpute for single-cell RNA-seq data | 87 | 8 | 79 | 9.2% |
| 0zj8s368 | Statistical Assumptions as Empirical Commitments | 86 | 57 | 29 | 66.3% |
| 4q74x3fr | The Foundations of Causal Inference | 86 | 13 | 73 | 15.1% |
| 6st1j18s | Growing impact of wildfire on western US water supply | 85 | 19 | 66 | 22.4% |
| 1gp5n7r0 | Methods for Inference from Respondent-Driven Sampling Data | 84 | 7 | 77 | 8.3% |
| 84j7c2w5 | Regression with Missing X's: A Review | 84 | 64 | 20 | 76.2% |
| 29w3z5b6 | Geometrical Aspects of Multiple Correspondence Analysis: Implications for the Coordinate Scaling Debate | 83 | 68 | 15 | 81.9% |
| 51v706k5 | Measuring Ethnic Bias: Can Misattribution-Based Tools from Social Psychology Reveal Group Biases that Economics Games Cannot? | 81 | 7 | 74 | 8.6% |
| 7786134t | Statistics and the Modern Student | 81 | 62 | 19 | 76.5% |
| 6k3027b9 | Kernel-Based Regularized Least Squares in R ( KRLS ) and Stata ( krls ) | 79 | 60 | 19 | 75.9% |
| 13k6x1w8 | Jakob Bernoulli's Theory of Inference | 78 | 6 | 72 | 7.7% |
| 1p3837fg | Understanding networks with exponential-family random network models | 78 | 44 | 34 | 56.4% |
| 7wg0k7xq | Applications of Convex Analysis to Multidimensional Scaling | 78 | 40 | 38 | 51.3% |
| 52b8201d | Decadal predictability of late winter precipitation in western Europe through an ocean–jet stream connection | 77 | 8 | 69 | 10.4% |
| 5m64m4p5 | Introduction to Special Edition: The Future of the Textbook | 77 | 6 | 71 | 7.8% |
| 8940b4k8 | Approximating the Distribution of Pareto Sums | 77 | 59 | 18 | 76.6% |
| 3r63h452 | Discussions | 76 | 1 | 75 | 1.3% |
| 6xc0172f | Isotone Optimization in R: Pool-Adjacent-Violators Algorithm (PAVA) and Active Set Methods | 76 | 60 | 16 | 78.9% |
| 3jq067x8 | Bounds on Treatment Effects from Studies with Imperfect Compliance | 75 | 27 | 48 | 36.0% |
Note: Due to the evolving nature of web traffic, the data presented here should be considered approximate and subject to revision. Learn more.