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| Deletions are marked like this. | Additions are marked like this. |
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| * [[Statistics/AverageAbsoluteDeviation|Average absolute deviation]] | |
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| * [[Statistics/CovarianceMatrices|Covariance matrices]] * [[Statistics/DegreesOfFreedom|Degrees of freedom]] |
* [[Statistics/Correlation|Correlation]] * [[Statistics/Logit|Logit]] |
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== Uncertainty == * [[Statistics/AverageAbsoluteDeviation|Average absolute deviation]] * [[Statistics/Covariance|Covariance]] * [[Statistics/DegreesOfFreedom|Degrees of freedom]] * [[Statistics/Variance|Variance]] * [[Statistics/PooledVariance|Pooled variance]] |
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| * [[Statistics/BayesianNotation|Bayesian notation]] | |
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| * [[Statistics/Independence|Independence]] | |
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| * [[Statistics/Logit|Logit]] * [[Statistics/ProbabilityNotation|Probability notation]] |
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== Prediction == * [[Statistics/BayesianNotation|Bayesian notation]] * [[Statistics/ConditionalExpectations|Conditional expectations]] * [[Statistics/ExpectedValues|Expected values]] * [[Statistics/Moments|Moments]] |
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| * [[Statistics/HotellingsTSquaredDistribution|Hotelling's T-squared]] * [[Statistics/MillsRatio|Mills' ratio]] |
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| * [[Statistics/FTest|F test]] * [[Statistics/GrangerCausalityTest|Granger causality test]] |
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| * [[Statistics/WaldWolfowitzRunsTest|Wald-Wolfowitz runs test]] | |
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== Prediction == * [[Statistics/ConditionalExpectations|Conditional expectations]] * [[Statistics/ExpectedValues|Expected values]] * [[Statistics/Moments|Moments]] |
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| * [[Statistics/IterativelyReweightedLeastSquares|IRLS]] | * [[Statistics/IterativelyReweightedLeastSquares|Iteratively reweighted least squares]] |
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| * [[Statistics/MaximumLikelihoodEstimation|maximum likelihood estimation]] | * [[Statistics/MaximumLikelihoodEstimation|Maximum likelihood estimation]] |
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| * [[Statistics/AutoregressiveModels|Autoregressive models]] * [[Statistics/DifferenceInDifferences|Difference in differences]] |
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| * [[Statistics/VectorAutoregression|Vector autoregression]] | |
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| * [[TheCommonStructureOfStatisticalModelsOfTruncationSampleSelectionAndLimitedDependentVariablesAndASimpleEstimatorForSuchModels|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 | |
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| * [[AComparisonOfMethodsOfWeightingAdjustmentForNonresponse|A Comparison of Methods of Weighting Adjustment for Nonresponse]], Graham Kalton and Dalisay S. Maligalig, 1991 | |
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| * [[ASimulationStudyOfCellCollapsingInPoststratification|A simulation study of cell collapsing in poststratification]]; Jay J. Kim, Linda Tompkins, Jianzhu Li, and Richard Valliant; 2005 | |
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| * [[PracticalConsiderationsInRakingSurveyData|Practical Considerations in Raking Survey Data]]; Michael P Battaglia, David C Hoaglin, and Martin R Frankel (and sometimes David Izrael); 2009 | |
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| * [[TheLawOfLargePopulationsDoesNotHeraldAParadigmShiftInSurveySampling|The “Law of Large Populations” Does Not Herald a Paradigm Shift in Survey Sampling]], Roderick J. Little, 2023 |
Statistics
A branch of mathematics.
Foundations
Uncertainty
Probability
Prediction
Probability distributions
Probability tests
Samples
Modeling
Econometrics
Psychometrics
Panel modeling
Non-parametric modeling
Survey analysis
Natural language processing
Reading Notes
Estimation of Relationships for Limited Dependent Variables, James Tobin, 1958
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
Measurement Error Models, Wayne A. Fuller, 1987
Latent Variable Modeling in Heterogeneous Populations, Bengt O. Muthén, 1989
A Comparison of Methods of Weighting Adjustment for Nonresponse, Graham Kalton and Dalisay S. Maligalig, 1991
The Effect of Weight Trimming on Nonlinear Survey Estimates, Frank J. Potter, 1993
Evidence on the Validity of Cross-sectional and Longitudinal Labor Market Data, John Bound, Charles Brown, Greg J. Duncan, and Willard L. Rodgers, 1994
Sampling Weights and Regression Analysis, Christopher Winship and Larry Radbill, 1994
Multilevel Covariance Structure Analysis, Bengt O. Muthén, 1994
Improving on Probability Weighting for Household Size, Andrew Gelman and Thomas C. Little, 1998
Statistical Modeling: The Two Cultures, Leo Breiman, 2001
Hierarchical Linear Models: Applications and Data Analysis Methods, Stephen W. Raudenbush and Anthony S. Bryk, 2002
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
Struggles with Survey Weighting and Regression Modeling, Andrew Gelman, 2007
The calibration approach in survey theory and practice, Carl-Erik Särndal, 2007
Practical Considerations in Raking Survey Data; Michael P Battaglia, David C Hoaglin, and Martin R Frankel (and sometimes David Izrael); 2009
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
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
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
Statistical Paradises and Paradoxes in Big Data, Xiao-Li Meng, 2018
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
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
A New Paradigm for Polling, Michael A. Bailey, 2023
The “Law of Large Populations” Does Not Herald a Paradigm Shift in Survey Sampling, Roderick J. Little, 2023
The effect of online interviews on the University of Michigan Survey of Consumer Sentiment, Ryan Cummings and Ernie Tedeschi, 2024
Measurement error when surveying issue positions: a MultiTrait MultiError approach; Kim Backström, Alexandru Cernat, Rasmus Sirén, and Peter Söderlund; 2025
Invitation Letters Increase Response Rates in Elite Surveys: Evidence from Germany and the United Kingdom, Nathalie Giger and Miguel M. Pereira, 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