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| == Estimation == * [[Statistics/DegreesOfFreedom|Degrees of freedom]] * [[Statistics/MaximumLikelihood|Maximum likelihood]] * [[Statistics/PooledVariance|Pooled variance]] |
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| * [[Statistics/DegreesOfFreedom|Degrees of freedom]] | |
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| * [[Statistics/Variance|Variance]] * [[Statistics/PooledVariance|Pooled variance]] |
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| * [[Statistics/Moments|Moments]] | |
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| * [[Statistics/SyntheticRespondents|Synthetic respondents]] | |
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| * [[IncreasingPrecisionWithoutAlteringTreatmentEffects|Increasing Precision without Altering Treatment Effects: Repeated Measures Designs in Survey Experiments]]; Scott Clifford, Geoffrey Sheagley, and Spencer Piston; 2021 | |
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| * [[ADesignForObservationalStudiesInWhichSomePeopleAvoidTreatment|A Design for Observational Studies in Which Some People Avoid Treatment]], Paul R. Rosenbaum, 2026 * [[AnalyzingTheImpactOfEventsThroughSurveys|Analyzing the impact of events through surveys: formalizing biases and introducing the dual randomized survey design]]; Andrew Bertoli, Laura Jakli, and Henry Pascoe; 2026 * [[NewEvidenceAndDesignConsiderationsForRepeatedMeasureExperimentsInSurveyResearch|New Evidence and Design Considerations for Repeated Measure Experiments in Survey Research]]; Diana Jordan, Trent Ollerenshaw, and Andrew Trexler; 2026 * [[DoubleRobustSmallAreaEstimation|Double-Robust Small Area Estimation]]; Haiqiang Ma, Zhiyan Sheng, and Jiming Jiang; 2026 * [[RespondentDrivenSamplingOnlineAsAStrategyToAccessHardToReachButNonHiddenPopulations|Respondent-Driven Sampling Online (Web Rds) as a Strategy to Access Hard-To-Reach But Non-Hidden Populations: The Case of Health Professionals Working in Chilean Schools]]; Katherine Dinamarca-Aravena, Andrés González Santa Cruz, Sonia Morales Miranda, Teresita Rocha Jiménez, and Álvaro Castillo-Carniglia; 2026 * [[ResponsibleAIIntegrationInSurveyResearch|Responsible AI Integration in Survey Research]]; David M. Rothschild, Jenny Marlar, Ashley Amaya, Soubhik Barari, Trent Buskirk, Curtiss Cobb, Jen Gennai, Sunshine Hillygus, Ramya Korlakai Vinayak, Masha Krupenkin, Sunghee Lee, Darby Steiger, and Brock Webb; 2026 |
Statistics
A branch of mathematics.
Foundations
Estimation
Uncertainty
Probability
Prediction
Tests
Samples
Modeling
Econometrics
Psychometrics
Structural equation modeling (and related reading notes)
Non-parametric modeling
Survey analysis
Survey nonresponse (and related reading notes)
Survey weights (and related reading notes)
Natural language processing
Reading Notes
Note: reading notes for the above topics are listed on the respective pages, not here.
On the Application of Probability Theory to Agricultural Experiments. Essay on Principles. Section 9, Jerzy Splawa-Neyman, 1923
On Statistics Independent of a Complete Sufficient Statistic, D. Basu, 1955
Estimation of Relationships for Limited Dependent Variables, James Tobin, 1958
Multiple Frame Surveys, H.O. Hartley, 1962
The Common Structure of Statistical Models of Truncation, Sample Selection and Limited Dependent Variables and a Simple Estimator for Such Models, James J. Heckman, 1976
Sequential Sample Selection Methods, James R. Chromy, 1979
The central role of the propensity score in observational studies for causal effects, Paul R. Rosenbaum and Donald B. Rubin, 1983
Sampling Rare Populations, Graham Kalton and Dallas W. Anderson, 1986
Measurement Error Models, Wayne A. Fuller, 1987
Comment: Neyman (1923) and Causal Inference in Experiments and Observational Studies, Donald B. Rubin, 1990
Evidence on the Validity of Cross-sectional and Longitudinal Labor Market Data, John Bound, Charles Brown, Greg J. Duncan, and Willard L. Rodgers, 1994
Estimation in Dual Frame Surveys With Complex Designs, J.N.K. Rao and C.J. Skinner, 1996
Statistical Modeling: The Two Cultures, Leo Breiman, 2001
Measurement Validity: A Shared Standard for Qualitative and Quantitative Research, Robert Adcock and David Collier, 2001
Double Sampling, Michael Hidiroglou, 2001
Hierarchical Linear Models: Applications and Data Analysis Methods, Stephen W. Raudenbush and Anthony S. Bryk, 2002
The influence of violations of assumptions on multilevel parameter estimates and their standard errors, Cora J.M. Maas and Joop J. Hox, 2003
Ascertaining the validity of individual protocols from Web-based personality inventories, John A. Johnson, 2004
A simulation study of cell collapsing in poststratification; Jay J. Kim, Linda Tompkins, Jianzhu Li, and Richard Valliant; 2005
Is OLS with a binary dependent variable really OK?: Estimating (mostly) TSCS models with binary dependent variables and fixed effects, Nathaniel Beck, 2011
Alternative survey sample designs: Sampling with multiple overlapping frames, Sharon L. Lohr, 2011
Identifying Careless Responses in Survey Data, Andrew Meade, S. Bartholomew Craig, 2012
Respondent use of straight-lining as a response strategy in education survey research: Prevalence and implications; James S. Cole, Alexander C. McCormick, Robert M. Gonyea; 2012
Estimating Measurement Error in Annual Job Earnings, John M. Abowd and Martha H. Stinson, 2013
Why ask why? Forward causal inference and reverse causal questions, Andrew Gelman and Guido Imbens, 2013
The Table 2 Fallacy: Presenting and Interpreting Confounder and Modifier Coefficients, Daniel Westreich and Sander Greenland, 2013
Beyond Power Calculations: Assessing Type S (Sign) and Type M (Magnitude) Errors, Andrew Gelman and John Carlin, 2014
How Robust Standard Errors Expose Methodological Problems They Do Not Fix, and What to Do About It, Gary King and Margaret E. Roberts, 2015
Straightlining in Web survey panels over time, Matthias Schonlau and Vera Toepoel, 2015
A Practitioner’s Guide to Cluster-Robust Inference, A. Colin Cameron and Douglas L. Miller, 2015
Imputation Under Informative Sampling; Emily Berg, Jae-Kwang Kim, and Chris Skinner; 2016
Conditional Probability Estimation, Marco E. G. V. Cattaneo, 2016
Sampling-based vs. Design-based Uncertainty in Regression Analysis; Alberto Abadie, Susan Athey, Guido W. Imbens, and Jeffrey M. Wooldridge; 2017
When Should You Adjust Standard Errors for Clustering?; Alberto Abadie, Susan Athey, Guido W. Imbens, and Jeffrey M. Wooldridge; 2017
Why Propensity Scores Should Not Be Used for Matching, Gary King and Richard Nielsen, 2019
Regression and Other Stories, Andrew Gelman, Jennifer Hill, and Aki Vehtari, 2020
Unexpected Event during Surveys Design: Promise and Pitfalls for Causal Inference; Jordi Muñoz, Albert Falcó-Gimeno, and Enrique Hernández; 2020
A Permutation Test on Complex Sample Data, Daniell Toth, 2020
Exact Adaptive Confidence Intervals for Small Areas, Kyle C. Burris and Peter D. Hoff, 2020
Increasing Precision without Altering Treatment Effects: Repeated Measures Designs in Survey Experiments; Scott Clifford, Geoffrey Sheagley, and Spencer Piston; 2021
The Independent Contractor Workforce: New Evidence on Its Size and Composition and Ways to Improve Its Measurement in Household Surveys; Katharine G. Abraham, Brad J. Hershbein, Susan N. Houseman, and Beth C. Truesdale; 2023
Using Hierarchical Models to Estimate Heterogeneous Effects, Joshua Alley, 2023
Out of One, Many: Using Language Models to Simulate Human Samples; Lisa P. Argyle, Ethan C. Busby, Nancy Fulda, Joshua R. Gubler, Christopher Rytting, and David Wingate; 2023
Causal Models for Longitudinal and Panel Data: A Survey, Dmitry Arkhangelsky and Guido Imbens, 2023
The Impact of Mixing Survey Modes on Estimates of Change: A Quasi-Experimental Study, Alexandru Cernat and Joseph W. Sakshaug, 2023
The effect of online interviews on the University of Michigan Survey of Consumer Sentiment, Ryan Cummings and Ernie Tedeschi, 2024
The micro-task market for lemons: data quality on Amazon’s Mechanical Turk; Douglas J. Ahler, Carolyn E. Roush, and Gaurav Sood; 2024
Adapting to Misspecification; Timothy B. Armstrong, Patrick Kline, and Liyang Sun; 2024
Linking Survey and LinkedIn Data: Understanding Usage and Consent Patterns; Tarek Al Baghal, Alexander Wenz, Paulo Serôdio, Shujin Liu, Curtis Jessop, and Luke Sloan; 2024
Small Area Prediction for Exponential Dispersion Families Under Informative Sampling, Emily Berg and Abdulhakeem Eideh, 2024
Area-Level Model-Based Small Area Estimation of Divergence Indexes in the Spanish Labour Force Survey; Esteban Cabello, Domingo Morales, Agustín Pérez; 2024
Text Messages to Facilitate the Transition to Web-First Sequential Mixed-Mode Designs in Longitudinal Surveys, Pablo Cabrera-Álvarez and Peter Lynn, 2024
Optimal Allocation Under Anticipated Nonresponse, Jonathan Mendelson and Michael R Elliott, 2024
Measurement error when surveying issue positions: a MultiTrait MultiError approach; Kim Backström, Alexandru Cernat, Rasmus Sirén, and Peter Söderlund; 2025
Self-Reporting News Use in Situ and in Retrospect; Danit Shalev, Teresa K Naab, and Yariv Tsfati; 2025
Where to place sensitive questions? Experiments on survey response order and measures of discriminatory attitudes; Amanda Sahar d’Urso, Tabitha Bonilla, and Genni Bogdanowicz; 2025
Difference-in-Differences Designs: A Practitioner’s Guide; Andrew Baker, Brantly Callaway, Scott Cunningham, Andrew Goodman-Bacon, and Pedro H. C. Sant’Anna; 2025
Inferring a Population Composition From Survey Data With Nonignorable Nonresponse: Borrowing Information From External Sources, Veronica Ballerini and Brunero Liseo, 2025
A New General Class of Discrete Bivariate Distributions Constructed by the Usual Stochastic Order; Min Ju Lee, Na Young Yoo, and Ji Hwan Cha; 2025
Linear Model Estimation and Prediction for p > n, Ronald Christensen, 2025
Nonparametric Block Bootstrap Kolmogorov-Smirnov Goodness-of-Fit Test; Mathew Chandy, Elizabeth D. Schifano, Jun Yan, and Xianyang Zhang; 2025
On Consistent Imputation of Missing Predictors in Linear Regression Models, David Oakes, 2025
Using Total Margin of Error to Account for Non-Sampling Error in Election Polls, Jeff Dominitz and Charles F. Manski, 2025
Visualizing Kendall’s τ and Hidden Structures in Ranked Data; Nicholas D. Edwards, Enzo de Jong, Feng Liu, and Stephen T. Ferguson; 2025
Bayesian Sample Size Calculations for External Validation Studies of Risk Prediction Models; Mohsen Sadatsafavi, Paul Gustafson, Solmaz Setayeshgar, Laure Wynants, and Richard D. Riley; 2026
How and when to use causal and associational language, Jeremy A Labrecque and Katrina L Kezios, 2026
On the Number of Replications in Resampling Tests and Monte Carlo Simulation Studies, Daniel Gaigall and Julian Gerstenberg, 2026
A Design for Observational Studies in Which Some People Avoid Treatment, Paul R. Rosenbaum, 2026
Analyzing the impact of events through surveys: formalizing biases and introducing the dual randomized survey design; Andrew Bertoli, Laura Jakli, and Henry Pascoe; 2026
New Evidence and Design Considerations for Repeated Measure Experiments in Survey Research; Diana Jordan, Trent Ollerenshaw, and Andrew Trexler; 2026
Double-Robust Small Area Estimation; Haiqiang Ma, Zhiyan Sheng, and Jiming Jiang; 2026
Respondent-Driven Sampling Online (Web Rds) as a Strategy to Access Hard-To-Reach But Non-Hidden Populations: The Case of Health Professionals Working in Chilean Schools; Katherine Dinamarca-Aravena, Andrés González Santa Cruz, Sonia Morales Miranda, Teresita Rocha Jiménez, and Álvaro Castillo-Carniglia; 2026
Responsible AI Integration in Survey Research; David M. Rothschild, Jenny Marlar, Ashley Amaya, Soubhik Barari, Trent Buskirk, Curtiss Cobb, Jen Gennai, Sunshine Hillygus, Ramya Korlakai Vinayak, Masha Krupenkin, Sunghee Lee, Darby Steiger, and Brock Webb; 2026