Department of Statistics, UCLA
Parent: UCLA
eScholarship stats: Breakdown by Item for October, 2024 through January, 2025
| Item | Title | Total requests | Download | View-only | %Dnld |
|---|---|---|---|---|---|
| 2mk8r49v | Comparative Fit Indices in Structural Models | 433 | 373 | 60 | 86.1% |
| 3sr461nd | Fixed and Random Effects in Panel Data Using Structural Equations Models | 368 | 35 | 333 | 9.5% |
| 583610fv | A Generalized Definition of the Polychoric Correlation Coefficient | 362 | 49 | 313 | 13.5% |
| 7qp4604r | The Phi-coefficient, the Tetrachoric Correlation Coefficient, and the Pearson-Yule Debate | 303 | 60 | 243 | 19.8% |
| 87t603ns | On Statistical Criteria: Theory, History, and Applications | 300 | 7 | 293 | 2.3% |
| 53n4f34m | Bayesian networks | 276 | 17 | 259 | 6.2% |
| 0pg6471b | Making sense of sensitivity: extending omitted variable bias | 253 | 146 | 107 | 57.7% |
| 6gv9n38c | Causal Diagrams for Empirical Research | 238 | 172 | 66 | 72.3% |
| 27s1d3h7 | Robust Statistical Modeling Using the t- Distribution | 221 | 132 | 89 | 59.7% |
| 6cn677bx | Comparative Fit Indices in Structural Models | 211 | 19 | 192 | 9.0% |
| 8cs5815x | Vision as Bayesian Inference: Analysis by Synthesis? | 202 | 73 | 129 | 36.1% |
| 9q6553kr | Object Perception as Bayesian Inference | 202 | 167 | 35 | 82.7% |
| 24w7k7m1 | Mahalanobis' Distance Beyond Normal Distributions | 193 | 6 | 187 | 3.1% |
| 6gr648np | Benchmarking Computational Doublet-Detection Methods for Single-Cell RNA Sequencing Data | 148 | 15 | 133 | 10.1% |
| 490131xj | The Causal Foundations of Structural Equation Modeling | 147 | 126 | 21 | 85.7% |
| 2bz9c0zr | Comparing Robust Properties of A, D, E and G-Optimal Designs | 136 | 7 | 129 | 5.1% |
| 3141h70c | Scaling Corrections for Statistics in Covariance Structure Analysis | 136 | 109 | 27 | 80.1% |
| 45x689gq | Identifiability of Path-Specific Effects | 116 | 30 | 86 | 25.9% |
| 4bp1t13z | Designing Studies for Dose Response | 112 | 3 | 109 | 2.7% |
| 49m7794d | A Comparison of Some Methodologies for the Factor Analysis of Non-Normal Likert Variables: A Note on the Size of the Model | 101 | 87 | 14 | 86.1% |
| 8940b4k8 | Approximating the Distribution of Pareto Sums | 98 | 67 | 31 | 68.4% |
| 65z429wc | Assessment and Propagation of Model Uncertainty | 96 | 20 | 76 | 20.8% |
| 13k6x1w8 | Jakob Bernoulli's Theory of Inference | 87 | 5 | 82 | 5.7% |
| 99b2s80w | Heider vs Simmel: Emergent Features in Dynamic Structures | 86 | 15 | 71 | 17.4% |
| 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 | 84 | 5 | 79 | 6.0% |
| 84j7c2w5 | Regression with Missing X's: A Review | 84 | 63 | 21 | 75.0% |
| 3s62r0d6 | Simpson's Paradox: An Anatomy | 82 | 67 | 15 | 81.7% |
| 51v706k5 | Measuring Ethnic Bias: Can Misattribution-Based Tools from Social Psychology Reveal Group Biases that Economics Games Cannot? | 82 | 2 | 80 | 2.4% |
| 05n729v1 | Homogeneity Analysis in R: The Package homals | 81 | 11 | 70 | 13.6% |
| 0fd986xb | Information Theory and an Extension of the Maximum Likelihood Principle by Hirotogu Akaike | 80 | 57 | 23 | 71.3% |
| 3tv1b3bg | Transportability across studies: A formal approach | 80 | 18 | 62 | 22.5% |
| 9nh0d6wj | Probabilities of Causation: Three Counterfactual Interpretations and their Identification | 80 | 5 | 75 | 6.3% |
| 80s9k72v | An accurate and robust imputation method scImpute for single-cell RNA-seq data | 79 | 2 | 77 | 2.5% |
| 5m64m4p5 | Introduction to Special Edition: The Future of the Textbook | 78 | 3 | 75 | 3.8% |
| 7wg0k7xq | Applications of Convex Analysis to Multidimensional Scaling | 78 | 39 | 39 | 50.0% |
| 3r63h452 | Discussions | 77 | 1 | 76 | 1.3% |
| 2cs5m2sh | A Primer on Robust Regression | 76 | 51 | 25 | 67.1% |
| 2hw5r3tm | Why There Is No Statistical Test for Confounding, Why Many Think There Is, and Why They Are Almost Right | 76 | 19 | 57 | 25.0% |
| 12m9z8c2 | The Racialization and Feminization of Poverty? | 75 | 21 | 54 | 28.0% |
| 6k3027b9 | Kernel-Based Regularized Least Squares in R ( KRLS ) and Stata ( krls ) | 75 | 61 | 14 | 81.3% |
| 6xc0172f | Isotone Optimization in R: Pool-Adjacent-Violators Algorithm (PAVA) and Active Set Methods | 75 | 65 | 10 | 86.7% |
| 29w3z5b6 | Geometrical Aspects of Multiple Correspondence Analysis: Implications for the Coordinate Scaling Debate | 72 | 66 | 6 | 91.7% |
| 2nt2p3dt | Bipartite tight spectral clustering (BiTSC) algorithm for identifying conserved gene co-clusters in two species. | 72 | 3 | 69 | 4.2% |
| 4q74x3fr | The Foundations of Causal Inference | 72 | 10 | 62 | 13.9% |
| 6st1j18s | Growing impact of wildfire on western US water supply | 72 | 8 | 64 | 11.1% |
| 6nx307ct | Comment | 71 | 0 | 71 | 0.0% |
| 9050x4r4 | Reproducible Research. The Bottom Line | 71 | 7 | 64 | 9.9% |
| 9zx0h8k6 | Aspects of Graphical Models Connected with Causality | 71 | 56 | 15 | 78.9% |
| 5pk7v8c5 | What are Textons? | 69 | 8 | 61 | 11.6% |
| 7tn3p6jx | Causal Diagrams | 68 | 60 | 8 | 88.2% |
Note: Due to the evolving nature of web traffic, the data presented here should be considered approximate and subject to revision. Learn more.