https://rss.onlinelibrary.wiley.com/doi/pdf/10.1111/j.2517-6161.1977.tb01600.x

Maximum likelihood from incomplete data via the EM algorithm

Valid predictions for the direction of nonresponse bias were obtained from subjective estimates and extrapolations in an analysis of mail survey data from published studies For estimates of the magnitude of bias, the use of extrapolations led to substantial improvements over a strategy of not using extrapolations

/pdf/estimating-nonresponse-bias-in-mail-surveys-5g9kpafflr.pdf

Estimating Nonresponse Bias in Mail Surveys

Validation of psychological tests has not yet been adequately conceptualized, as the APA Committee on Psychological Tests learned when it undertook (1950-54) to specify what qualities should be investigated before a test is published. In order to make coherent recommendations the Committee found it necessary to distinguish four types of validity, established by different types of research and requiring different interpretation. The chief innovation in the Committee's report was the term construct validity.[2] This idea was first formulated by a subcommittee (Meehl and R. C. Challman) studying how proposed recommendations would apply to projective techniques, and later modified and clarified by the entire Committee (Bordin, Challman, Conrad, Humphreys, Super, and the present writers). The statements agreed upon by the Committee (and by committees of two other associations) were published in the Technical Recommendations (59). The present interpretation of construct validity is not "official" and deals with some areas where the Committee would probably not be unanimous. The present writers are solely responsible for this attempt to explain the concept and elaborate its implications.

/pdf/construct-validity-in-psychological-tests-1tuszfx7to.pdf

Construct validity in psychological tests.

Valid predictions for the direction of nonresponse bias were obtained from subjective estimates and extrapolations in an analysis of mail survey data from published studies. For estimates of the magnitude of bias, the use of extrapolations led to substantial improvements over a strategy of not using extrapolations.

Statistical approaches to processing natural language text have become dominant in recent years This foundational text is the first comprehensive introduction to statistical natural language processing (NLP) to appear The book contains all the theory and algorithms needed for building NLP tools It provides broad but rigorous coverage of mathematical and linguistic foundations, as well as detailed discussion of statistical methods, allowing students and researchers to construct their own implementations The book covers collocation finding, word sense disambiguation, probabilistic parsing, information retrieval, and other applications

/pdf/foundations-of-statistical-natural-language-processing-1ou5e6c2q6.pdf

Foundations of Statistical Natural Language Processing

The 1964 publication of "Inference and Disputed Authorship" made the cover of "Time" magazine and drew the attention of academics and the public alike for its use of statistical methodology to solve one of American history's most notorious questions: the disputed authorship of the "Federalist Papers". Back in print for a new generation of readers, this classic volume applies mathematics, including the once-controversial Bayesian analysis, to the heart of a literary and historical problem by studying frequently used words in the texts. The reissue of this landmark book will be welcomed by anyone interested in the juncture of history, political science, and authorship.

Inference and disputed authorship : The Federalist

Inference and Disputed Authorship: The Federalist

This study has four purposes: to provide a comparison of discrimination methods; to explore the problems presented by techniques based strongly on Bayes' theorem when they are used in a data analysis of large scale; to solve the authorship question of The Federalist papers; and to propose routine methods for solving other authorship problems. Word counts are the variables used for discrimination. Since the topic written about heavily influences the rate with which a word is used, care in selection of words is necessary. The filler words of the language such as an, of, and upon, and, more generally, articles, prepositions, and conjunctions provide fairly stable rates, whereas more meaningful words like war, executive, and legislature do not. After an investigation of the distribution of these counts, the authors execute an analysis employing the usual discriminant function and an analysis based on Bayesian methods. The conclusions about the authorship problem are that Madison rather than Hamilton ...

Inference in an Authorship Problem

Applied Bayesian and Classical Inference: The Case of The Federalist Papers

/pdf/asymptotic-approximations-to-distributions-1ly5nx7pr7.pdf

David L. Wallace

Papers

Inference and disputed authorship : The Federalist

Inference and Disputed Authorship: The Federalist

Inference in an Authorship Problem

Applied Bayesian and Classical Inference: The Case of The Federalist Papers

Asymptotic Approximations to Distributions