Statistical Models: Theory and Practice: References

By David Freedman. 2005

1,553 citations recorded by the source corpus.

View Paper: https://www.semanticscholar.org/paper/aca94fc2282885497b903bb0d2930bc7caad35e4

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Citations in the corpus

Finding Expert Authors in Financial Forum Using Deep Learning Methods (2018, methodology): “We applied logistic regression [7] on the StockTwits dataset and use unigrams as features.”
Big Data: Deep Learning for financial sentiment analysis (2018, methodology): “We follow Wang [2] approach and apply logistic regression [3] on the StockTwits dataset.”
Pesticide use and risk perceptions among farmers in the cotton belt of Punjab, Pakistan (2015, methodology): “A probit regression model designed to analyze response variables with only two outcomes (Freedman, 2009) was used to describe farmers' overuse behavior (OUB) as an endogenous dummy variable.”
On regression adjustments to experimental data (2008, methodology): “In this example, the models seem to lack adequate substantive foundations, and were somewhat post hoc, as noted by Petitti and Freedman [19].”
Yelp Dataset Challenge: Review Rating Prediction (2016, background): “In logistic regression (Freedman, 2009), the conditional probability function P ( s | r ) is modelled, where r is a feature vector for review r and s belongs to the set of class labels { 1 , 2 , 3 , 4 , 5 } .”
Earthquake clusters in southern California I: Identification and stability (2013, methodology): “The cluster size seems to be independent of the mainshock magnitude; this visual impression is confirmed by the ANOVA [Freedman, 2005] and Kruskal-Wallis [Kruskal and Wallis, 1952] tests summarized in Table 4.”
CAUSAL INTERPRETATIONS OF BLACK-BOX MODELS (2019, unknown): “Suppose a student’s grade is determined by the hours she studied via where the noise variable (cid:2) is independent of “Hours studied.””
Statistical Procedures for Forecasting Criminal Behavior (2013, background): “An excellent, accessible, and technically sound treatment can be found in David Freedman’s textbook Statistical Models (2005). We cannot rehash the issues here except to stress that machine learning is not a form of structural equation modeling and should never be interpreted as such.”
On The So-Called “Huber Sandwich Estimator” and “Robust Standard Errors” (2006, background): “For a more general discussion of independence assumptions, see Berk and Freedman (2003) or Freedman (2005).”