Department of Statistics, UCLA
Parent: UCLA
eScholarship stats: Breakdown by Item for December, 2024 through March, 2025
| Item | Title | Total requests | Download | View-only | %Dnld |
|---|---|---|---|---|---|
| 2mk8r49v | Comparative Fit Indices in Structural Models | 451 | 412 | 39 | 91.4% |
| 583610fv | A Generalized Definition of the Polychoric Correlation Coefficient | 373 | 48 | 325 | 12.9% |
| 3sr461nd | Fixed and Random Effects in Panel Data Using Structural Equations Models | 337 | 29 | 308 | 8.6% |
| 87t603ns | On Statistical Criteria: Theory, History, and Applications | 323 | 9 | 314 | 2.8% |
| 7qp4604r | The Phi-coefficient, the Tetrachoric Correlation Coefficient, and the Pearson-Yule Debate | 318 | 66 | 252 | 20.8% |
| 6gv9n38c | Causal Diagrams for Empirical Research | 280 | 200 | 80 | 71.4% |
| 53n4f34m | Bayesian networks | 277 | 32 | 245 | 11.6% |
| 0pg6471b | Making sense of sensitivity: extending omitted variable bias | 264 | 153 | 111 | 58.0% |
| 6cn677bx | Comparative Fit Indices in Structural Models | 234 | 30 | 204 | 12.8% |
| 27s1d3h7 | Robust Statistical Modeling Using the t- Distribution | 233 | 146 | 87 | 62.7% |
| 490131xj | The Causal Foundations of Structural Equation Modeling | 172 | 159 | 13 | 92.4% |
| 9q6553kr | Object Perception as Bayesian Inference | 172 | 141 | 31 | 82.0% |
| 24w7k7m1 | Mahalanobis' Distance Beyond Normal Distributions | 171 | 8 | 163 | 4.7% |
| 3141h70c | Scaling Corrections for Statistics in Covariance Structure Analysis | 164 | 130 | 34 | 79.3% |
| 6gr648np | Benchmarking Computational Doublet-Detection Methods for Single-Cell RNA Sequencing Data | 155 | 14 | 141 | 9.0% |
| 8cs5815x | Vision as Bayesian Inference: Analysis by Synthesis? | 153 | 52 | 101 | 34.0% |
| 2bz9c0zr | Comparing Robust Properties of A, D, E and G-Optimal Designs | 124 | 8 | 116 | 6.5% |
| 8940b4k8 | Approximating the Distribution of Pareto Sums | 115 | 70 | 45 | 60.9% |
| 84j7c2w5 | Regression with Missing X's: A Review | 107 | 74 | 33 | 69.2% |
| 45x689gq | Identifiability of Path-Specific Effects | 106 | 21 | 85 | 19.8% |
| 9050x4r4 | Reproducible Research. The Bottom Line | 104 | 6 | 98 | 5.8% |
| 3tv1b3bg | Transportability across studies: A formal approach | 98 | 19 | 79 | 19.4% |
| 49m7794d | A Comparison of Some Methodologies for the Factor Analysis of Non-Normal Likert Variables: A Note on the Size of the Model | 94 | 82 | 12 | 87.2% |
| 0fd986xb | Information Theory and an Extension of the Maximum Likelihood Principle by Hirotogu Akaike | 91 | 62 | 29 | 68.1% |
| 99b2s80w | Heider vs Simmel: Emergent Features in Dynamic Structures | 89 | 17 | 72 | 19.1% |
| 3s62r0d6 | Simpson's Paradox: An Anatomy | 87 | 62 | 25 | 71.3% |
| 4bp1t13z | Designing Studies for Dose Response | 86 | 5 | 81 | 5.8% |
| 05n729v1 | Homogeneity Analysis in R: The Package homals | 85 | 12 | 73 | 14.1% |
| 6st1j18s | Growing impact of wildfire on western US water supply | 81 | 9 | 72 | 11.1% |
| 2nt2p3dt | Bipartite tight spectral clustering (BiTSC) algorithm for identifying conserved gene co-clusters in two species. | 80 | 5 | 75 | 6.3% |
| 7tn3p6jx | Causal Diagrams | 80 | 57 | 23 | 71.3% |
| 4cg0k6g0 | Determination of Sample Size for Multilevel Model Design | 79 | 36 | 43 | 45.6% |
| 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 | 79 | 3 | 76 | 3.8% |
| 7wg0k7xq | Applications of Convex Analysis to Multidimensional Scaling | 79 | 41 | 38 | 51.9% |
| 8zt041cg | Cerebral amyloid-beta plaques link host genotypes to neurocognitive impairment among HIV-infected adults | 79 | 77 | 2 | 97.5% |
| 5pk7v8c5 | What are Textons? | 77 | 9 | 68 | 11.7% |
| 65z429wc | Assessment and Propagation of Model Uncertainty | 77 | 14 | 63 | 18.2% |
| 4nm8w17x | A Bootstrap Lasso + Partial Ridge Method to Construct Confidence Intervals for Parameters in High-dimensional Sparse Linear Models | 76 | 55 | 21 | 72.4% |
| 80s9k72v | An accurate and robust imputation method scImpute for single-cell RNA-seq data | 76 | 1 | 75 | 1.3% |
| 9nh0d6wj | Probabilities of Causation: Three Counterfactual Interpretations and their Identification | 75 | 9 | 66 | 12.0% |
| 0t96w00k | A new record minimum for Antarctic sea ice | 74 | 20 | 54 | 27.0% |
| 4bq0g49v | Insights from Earth system model initial-condition large ensembles and future prospects | 73 | 15 | 58 | 20.5% |
| 52b8201d | Decadal predictability of late winter precipitation in western Europe through an ocean–jet stream connection | 73 | 13 | 60 | 17.8% |
| 52t9g8rz | Global progress and backsliding on gasoline taxes and subsidies | 73 | 15 | 58 | 20.5% |
| 5qk1s0dv | Object Perception as Bayesian Inference | 72 | 59 | 13 | 81.9% |
| 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? | 72 | 5 | 67 | 6.9% |
| 0zj8s368 | Statistical Assumptions as Empirical Commitments | 71 | 37 | 34 | 52.1% |
| 4q74x3fr | The Foundations of Causal Inference | 71 | 12 | 59 | 16.9% |
| 12m9z8c2 | The Racialization and Feminization of Poverty? | 70 | 16 | 54 | 22.9% |
| 6cs342k2 | Myth, Confusion, and Science in Causal Analysis | 70 | 17 | 53 | 24.3% |
Note: Due to the evolving nature of web traffic, the data presented here should be considered approximate and subject to revision. Learn more.