Department of Statistics, UCLA
Parent: UCLA
eScholarship stats: History by Item for March through June, 2025
Item | Title | Total requests | 2025-06 | 2025-05 | 2025-04 | 2025-03 |
---|---|---|---|---|---|---|
27s1d3h7 | Robust Statistical Modeling Using the t- Distribution | 583 | 96 | 355 | 70 | 62 |
490131xj | The Causal Foundations of Structural Equation Modeling | 560 | 37 | 72 | 384 | 67 |
331047wt | Characterizing Bias in Population Genetic Inferences from Low-Coverage Sequencing Data | 521 | 34 | 15 | 463 | 9 |
6gv9n38c | Causal Diagrams for Empirical Research | 464 | 77 | 246 | 63 | 78 |
2mk8r49v | Comparative Fit Indices in Structural Models | 458 | 82 | 121 | 119 | 136 |
7qp4604r | The Phi-coefficient, the Tetrachoric Correlation Coefficient, and the Pearson-Yule Debate | 425 | 87 | 158 | 92 | 88 |
3sr461nd | Fixed and Random Effects in Panel Data Using Structural Equations Models | 360 | 85 | 102 | 94 | 79 |
87t603ns | On Statistical Criteria: Theory, History, and Applications | 355 | 58 | 128 | 67 | 102 |
583610fv | A Generalized Definition of the Polychoric Correlation Coefficient | 346 | 80 | 79 | 72 | 115 |
8940b4k8 | Approximating the Distribution of Pareto Sums | 335 | 58 | 142 | 103 | 32 |
4r37990g | Multi-dimensional Point Process Models for Evaluating a Wildfire Hazard Index | 332 | 27 | 106 | 194 | 5 |
53n4f34m | Bayesian networks | 287 | 48 | 82 | 89 | 68 |
6cn677bx | Comparative Fit Indices in Structural Models | 258 | 42 | 80 | 69 | 67 |
0pg6471b | Making sense of sensitivity: extending omitted variable bias | 236 | 61 | 64 | 56 | 55 |
24w7k7m1 | Mahalanobis' Distance Beyond Normal Distributions | 205 | 42 | 71 | 53 | 39 |
3141h70c | Scaling Corrections for Statistics in Covariance Structure Analysis | 188 | 44 | 41 | 53 | 50 |
6gr648np | Benchmarking Computational Doublet-Detection Methods for Single-Cell RNA Sequencing Data | 184 | 58 | 41 | 42 | 43 |
8cs5815x | Vision as Bayesian Inference: Analysis by Synthesis? | 180 | 42 | 64 | 37 | 37 |
9q6553kr | Object Perception as Bayesian Inference | 169 | 38 | 50 | 37 | 44 |
4d7477sq | Estimation of the upper cutoff parameter for the tapered Pareto distribution | 151 | 18 | 65 | 57 | 11 |
9nh0d6wj | Probabilities of Causation: Three Counterfactual Interpretations and their Identification | 142 | 39 | 70 | 15 | 18 |
6qg1r096 | Cooling of US Midwest summer temperature extremes from cropland intensification | 132 | 21 | 35 | 67 | 9 |
45h3t3t2 | Bias in Factor Score Regression and a Simple Solution | 125 | 59 | 22 | 33 | 11 |
52t9g8rz | Global progress and backsliding on gasoline taxes and subsidies | 123 | 36 | 48 | 19 | 20 |
8n57f107 | Image Parsing: Unifying Segmentation, Detection, and Recognition | 123 | 28 | 73 | 14 | 8 |
0fd986xb | Information Theory and an Extension of the Maximum Likelihood Principle by Hirotogu Akaike | 117 | 29 | 21 | 35 | 32 |
84j7c2w5 | Regression with Missing X's: A Review | 117 | 29 | 33 | 24 | 31 |
0789f7d3 | The Gifi System for Nonlinear Multivariate Analysis | 115 | 64 | 19 | 15 | 17 |
38m3m5pq | On Principal Hessian Directions for Data Visualization and Dimension Reduction: Another Application of Stein's Lemma | 112 | 21 | 64 | 21 | 6 |
4bq0g49v | Insights from Earth system model initial-condition large ensembles and future prospects | 112 | 37 | 40 | 16 | 19 |
4cg0k6g0 | Determination of Sample Size for Multilevel Model Design | 112 | 43 | 12 | 21 | 36 |
2cs5m2sh | A Primer on Robust Regression | 110 | 41 | 31 | 23 | 15 |
4q74x3fr | The Foundations of Causal Inference | 110 | 30 | 33 | 26 | 21 |
0zj8s368 | Statistical Assumptions as Empirical Commitments | 107 | 44 | 27 | 20 | 16 |
7qw8m94p | The Farm Animal Genotype–Tissue Expression (FarmGTEx) Project | 107 | 39 | 68 | ||
18j2x5zr | An Introduction to Causal Inference | 105 | 24 | 66 | 9 | 6 |
23c604tb | A Scaled Difference Chi-square Test Statistic for Moment Structure Analysis | 105 | 18 | 62 | 17 | 8 |
3tv1b3bg | Transportability across studies: A formal approach | 105 | 29 | 26 | 30 | 20 |
7tn3p6jx | Causal Diagrams | 105 | 30 | 30 | 20 | 25 |
0tg4t8bd | Recent Developments in Causal Inference and Machine Learning | 101 | 46 | 34 | 10 | 11 |
2rj412j3 | Mate with the two Bishops in Kriegspiel | 101 | 32 | 36 | 26 | 7 |
9qf971fw | An Introduction to Causal Inference | 101 | 14 | 78 | 9 | |
76f0d1qz | Ensuring Positiveness of the Scaled Difference Chi-square Test Statistic | 100 | 40 | 56 | 4 | |
0hz9x8pc | The Mediation Formula: A guide to the assessment of causal pathways in nonlinear models | 99 | 32 | 32 | 19 | 16 |
12m9z8c2 | The Racialization and Feminization of Poverty? | 99 | 18 | 30 | 33 | 18 |
2fc64719 | Comment on “Data Fission: Splitting a Single Data Point” Data Fission for Unsupervised Learning: A Discussion on Post-Clustering Inference and the Challenges of Debiasing | 99 | 24 | 75 | ||
1gf0b3m7 | Simple and Canonical Correspondence Analysis Using the R Package anacor | 97 | 52 | 18 | 12 | 15 |
2nt2p3dt | Bipartite tight spectral clustering (BiTSC) algorithm for identifying conserved gene co-clusters in two species. | 97 | 38 | 18 | 21 | 20 |
5pk7v8c5 | What are Textons? | 97 | 42 | 25 | 18 | 12 |
8785j295 | Controlling Selection Bias in Causal Inference | 96 | 18 | 67 | 10 | 1 |
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