Linear Statistical Inference and its Applications: Second Editon

Maximum Likelihood from Incomplete Data Via the EM Algorithm

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A heteroskedasticity-consistent covariance matrix estimator and a direct test for heteroskedasticity

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STATISTICAL ANALYSIS OF COINTEGRATION VECTORS

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Asymptotic Confidence Intervals for Indirect Effects in Structural Equation Models

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Least angle regression

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Bootstrap Methods for Standard Errors, Confidence Intervals, and Other Measures of Statistical Accuracy

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A note on a general definition of the coefficient of determination

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A Simple Test for Heteroscedasticity and Random Coefficient Variation

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A scaled difference chi-square test statistic for moment structure analysis

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CONDENSATION—Conditional Density Propagation for Visual Tracking

Isard, M., & Blake, A. (1998) · International Journal of Computer Vision · doi:10.1023/a:1008078328650 · Cited by 4,886

Cox’s regression model for counting processes: A large sample study

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Beta regression for modelling rates and proportions

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The coefficient of determination R 2 and intra-class correlation coefficient from generalized linear mixed-effects models revisited and expanded

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Maximum Likelihood Approaches to Variance Component Estimation and to Related Problems

Harville, D. A. (1977) · Journal of the American Statistical Association · doi:10.1080/01621459.1977.10480998 · Cited by 2,667

Marginal Maximum Likelihood Estimation of Item Parameters: Application of an EM Algorithm

Bock, R. D., & Aitkin, M. (1981) · Psychometrika · doi:10.1007/bf02293801 · Cited by 2,339

Robust variance estimation in meta‐regression with dependent effect size estimates

Hedges, L. V., Tipton, E., & Johnson, M. C. (2010) · Research Synthesis Methods · doi:10.1002/jrsm.5 · Cited by 2,086

Bayes Estimates for the Linear Model

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Untitled work

Tufford (2017) · doi:10.1007/s · Cited by 2,003

A Reality Check for Data Snooping

White, H. (2000) · Econometrica · doi:10.1111/1468-0262.00152 · Cited by 1,851

Set correlation and contingency tables

Cohen, J. (1988) · Applied Psychological Measurement · doi:10.1177/014662168801200410 · Cited by 1,825

Conceptualizing and testing random indirect effects and moderated mediation in multilevel models: New procedures and recommendations.

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Clinical versus mechanical prediction: a meta-analysis

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Group representations in probability and statistics

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Direct and Indirect Effects: Classical and Bootstrap Estimates of Variability

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The Estimation of Choice Probabilities from Choice Based Samples

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Logistic regression, survival analysis, and the Kaplan-Meier curve.

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On the Variances of Asymptotically Normal Estimators from Complex Surveys

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Assessing the accuracy of the maximum likelihood estimator: Observed versus expected Fisher information

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Conditions under Which Mean Square Ratios in Repeated Measurements Designs Have Exact F-Distributions

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Familial Studies of Intelligence: A Review

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Estimating parameters of the diffusion model: Approaches to dealing with contaminant reaction times and parameter variability

Ratcliff, R., & Tuerlinckx, F. (2002) · Psychonomic Bulletin & Review · doi:10.3758/bf03196302 · Cited by 838

A Statistical Model for Positron Emission Tomography

Vardi, Y., Shepp, L. A., & Kaufman, L. (1985) · Journal of the American Statistical Association · doi:10.1080/01621459.1985.10477119 · Cited by 863

Nonparametric maximum likelihood estimation of a mixing distribution

Laird, N. (1978) · Journal of the American Statistical Association · doi:10.1080/01621459.1978.10480103 · Cited by 753

Interpreting Neuronal Population Activity by Reconstruction: Unified Framework With Application to Hippocampal Place Cells

Zhang, K., Ginzburg, I., McNaughton, B. L., & Sejnowski, T. J. (1998) · Journal of Neurophysiology · doi:10.1152/jn.1998.79.2.1017 · Cited by 741

The Analysis of Permutations

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Risk of childhood undernutrition related to small-for-gestational age and preterm birth in low- and middle-income countries

Christian, P., Lee, S. E., Donahue Angel, M., Adair, L. S., Arifeen, S. E., Ashorn, P., Barros, F. C., Fall, C. H., Fawzi, W. W., Hao, W., et al. (2013) · International Journal of Epidemiology · doi:10.1093/ije/dyt109 · Cited by 582

Regression and ordered categorical variables

Anderson, J. A. (1984) · Journal of the Royal Statistical Society Series B: Statistical Methodology · doi:10.1111/j.2517-6161.1984.tb01270.x · Cited by 574

On The So-Called “Huber Sandwich Estimator” and “Robust Standard Errors”

Freedman, D. A. (2006) · The American Statistician · doi:10.1198/000313006x152207 · Cited by 498

Allostatic load as a predictor of functional decline

Karlamangla, A. S., Singer, B. H., McEwen, B. S., Rowe, J. W., & Seeman, T. E. (2002) · Journal of Clinical Epidemiology · doi:10.1016/s0895-4356(02)00399-2 · Cited by 483

Standard Errors and Sample Sizes for Two-Level Research

Snijders, T. A. B., & Bosker, R. J. (1993) · Journal of Educational Statistics · doi:10.3102/10769986018003237 · Cited by 487

The Problem of the Placebo Response in Clinical Trials for Psychiatric Disorders: Culprits, Possible Remedies, and a Novel Study Design Approach

Fava, M., Evins, A. E., Dorer, D. J., & Schoenfeld, D. A. (2003) · Psychotherapy and Psychosomatics · doi:10.1159/000069738 · Cited by 452

Measuring inter-rater reliability for nominal data – which coefficients and confidence intervals are appropriate?

Zapf, A., Castell, S., Morawietz, L., & Karch, A. (2016) · BMC Medical Research Methodology · doi:10.1186/s12874-016-0200-9 · Cited by 377

Confidence Distribution, the Frequentist Distribution Estimator of a Parameter: A Review

Xie, M., & Singh, K. (2013) · International Statistical Review · doi:10.1111/insr.12000 · Cited by 319

Is there a threshold level of fetal hemoglobin that ameliorates morbidity in sickle cell anemia?

Powars, D., Weiss, J., Chan, L., & Schroeder, W. (1984) · Blood · doi:10.1182/blood.v63.4.921.921 · Cited by 314

PCA consistency in high dimension, low sample size context

Jung, S., & Marron, J. S. (2009) · The Annals of Statistics · doi:10.1214/09-aos709 · Cited by 303

Teaching about Approximate Confidence Regions Based on Maximum Likelihood Estimation

Meeker, W. Q., & Escobar, L. A. (1995) · The American Statistician · doi:10.1080/00031305.1995.10476112 · Cited by 279

Inference with dependent data using cluster covariance estimators

Bester, C. A., Conley, T. G., & Hansen, C. B. (2011) · Journal of Econometrics · doi:10.1016/j.jeconom.2011.01.007 · Cited by 258

Verifying the Solution from a Nonlinear Solver: A Case Study

McCullough, B. D., & Vinod, H. D. (2003) · American Economic Review · doi:10.1257/000282803322157133 · Cited by 220

REM and NREM sleep reports: comparison of word frequencies by cognitive classes

Antrobus, J. (1983) · Psychophysiology · doi:10.1111/j.1469-8986.1983.tb03015.x · Cited by 215

Maximum entropy autoregressive conditional heteroskedasticity model

Park, S. Y., & Bera, A. K. (2009) · Journal of Econometrics · doi:10.1016/j.jeconom.2008.12.014 · Cited by 218

Gene admixture in human populations: Models and predictions

Chakraborty, R. (1986) · American Journal of Physical Anthropology · doi:10.1002/ajpa.1330290502 · Cited by 218

The effect of nonnormality on some multivariate tests and robustness to nonnormality in the linear model

MARDIA, K. V. (1971) · Biometrika · doi:10.1093/biomet/58.1.105 · Cited by 223

Quantifying and correcting for the winner's curse in genetic association studies

Xiao, R., & Boehnke, M. (2009) · Genetic Epidemiology · doi:10.1002/gepi.20398 · Cited by 192

Effect of a cognitive behavioral intervention on reducing symptom severity during chemotherapy

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Changes in membrane potential during the progression of MCF‐7 human mammary tumor cells through the cell cycle

Wonderlin, W. F., Woodfork, K. A., & Strobl, J. S. (1995) · Journal of Cellular Physiology · doi:10.1002/jcp.1041650121 · Cited by 148

Surface orientation from texture: ideal observers, generic observers and the information content of texture cues

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Associations Between Suicidal High School Students’ Help-Seeking and Their Attitudes and Perceptions of Social Environment

Pisani, A. R., Schmeelk-Cone, K., Gunzler, D., Petrova, M., Goldston, D. B., Tu, X., & Wyman, P. A. (2012) · Journal of Youth and Adolescence · doi:10.1007/s10964-012-9766-7 · Cited by 138

Quantum Metrological Limits via a Variational Approach

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Changes in sleep patterns and depressive symptoms in first-time mothers: last trimester to 1-year postpartum

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DLATK: Differential Language Analysis ToolKit

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Some Statistical Results in the Combination of Forecasts

Dickinson, J. P. (1973) · Journal of the Operational Research Society · doi:10.1057/jors.1973.42 · Cited by 120

Classification of intended phoneme production from chronic intracortical microelectrode recordings in speech-motor cortex

Brumberg (2011) · Frontiers in Neuroscience · doi:10.3389/fnins.2011.00065 · Cited by 114

Practical methods for computing power in testing the multivariate general linear hypothesis

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Longitudinal stability of latent means and individual differences: A unified approach

Marsh, H. W., & Grayson, D. (1994) · Structural Equation Modeling: A Multidisciplinary Journal · doi:10.1080/10705519409539984 · Cited by 94

The importance of efficient use in the adoption of technology: A micro panel data analysis

Kalirajan, K. P. (1991) · Journal of Productivity Analysis · doi:10.1007/bf00156342 · Cited by 92

Statistical assessment of mediational effects for logistic mediational models

Huang, B., Sivaganesan, S., Succop, P., & Goodman, E. (2004) · Statistics in Medicine · doi:10.1002/sim.1847 · Cited by 89

Regression Estimation after Correcting for Attenuation

Fuller, W. A., & Hidiroglou, M. A. (1978) · Journal of the American Statistical Association · doi:10.1080/01621459.1978.10480011 · Cited by 90

Quantum Metrology for Noisy Systems

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Are Robust Standard Errors the Best Approach for Interval Estimation With Nonnormal Data in Structural Equation Modeling?

Falk, C. F. (2018) · Structural Equation Modeling: A Multidisciplinary Journal · doi:10.1080/10705511.2017.1367254 · Cited by 75

Digital health technologies and machine learning augment patient reported outcomes to remotely characterise rheumatoid arthritis

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Robustness to nonnormality of regression F-tests

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Combined result and associated uncertainty from interlaboratory evaluations based on the ISO Guide

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Specification tests for the propensity score

Sant’Anna, P. H. C., & Song, X. (2019) · Journal of Econometrics · doi:10.1016/j.jeconom.2019.02.002 · Cited by 31

Mianserin and chronic pain: a double-blind placebo-controlled process and outcome study

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On the Relationship Between Maximal Reliability and Maximal Validity of Linear Composites

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Statistical models of visual shape and motion

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Data Glitches: Monsters in Your Data

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Calcium fluxes at the bone/plasma interface: Acute effects of parathyroid hormone (PTH) and targeted deletion of PTH/PTH-related peptide (PTHrP) receptor in the osteocytes

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Use of Support Vector Machines to Assign Short-Term Counts to Seasonal Adjustment Factor Groups

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Determining the Rank of the Beta Matrix in Linear Asset Pricing Models

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