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Hypothesis testing and model selection in the social sciences
In: Methodology in the social sciences
1.HYPOTHESIS TESTING AND MODEL SELECTION p. 1 --1.1Introduction, p.1 --1.2Standard Procedure of Hypothesis Testing, p.4 --1.3Model Selection, p.9 --1.4Purpose and Plan of the Book, p.10 --2.HYPOTHESIS TESTING: CRITICISMS AND ALTERNATIVES p.12 --2.1Hypothesis Testing ad Its Discontents, p.12 --2.2Uses of Hypothesis Tests, p.13 --2.3Criticisms of Conventional Hypothesis Testing, p.17 --2.4Implications of the Criticisms, p.26 --2.5Alternatives to Conventional Tests, p.27 --2.6Examples, p.29 --2.7Summary and Conclusions, p.41 --Recommended Reading, p.42 --3.THE CLASSICAL APPROACH p.43 --3.1Random Sampling and Classical Tests, p.43 --3.2Two Approaches to Hypothesis Tests, p.46 --3.3Confidence Intervals, p.51 --3.4Choosing a Significance Level, p.53 --3.5Comparison to Conventional Practice, p.61 --3.6Implications of Choosing an a Level, p.63 --3.7Other Kinds of Errors, p.65 --3.8Example of Choosing an a Level, p.67 --3.9Evaluation of Criticisms, p.68 --3.10Summary and Conclusions, p.72 --Recommended Reading, p.74 --4.BAYESIAN HYPOTHESIS TESTS p.75 --4.1Bayes's Theorem, p.75 --4.2Bayesian Estimation, p.77 --4.3Bayes Factors, p.80 --4.4Bayesian Confidence Intervals and Bayes Factors, p.88 --4.5Approaches to Bayesian Hypothesis Testing, p.91 --4.6The Unit Information Prior, p.92 --4.7Limits on bayes Factors, p.97 --4.8Bayes Factors for Multiple Parameters, p.102 --4.9Summary and Conclusions, p.105Recommended Reading, p.106
Model selection
In: Sociological methods & research 33.2004/2005,2
In: Special issue
Comment: Evidence, Plausibility, and Model Selection
In: Sociological methodology, Band 48, Heft 1, S. 88-91
ISSN: 1467-9531
Book Review: Dunterman, George H. and Moon-Ho R. Ho. 2006. An Introduction to Generalized Linear Models (Quantitative Applications in the Social Sciences, Volume 145). Thousand Oaks, CA: Sage Publications. 88 pp. $17.95. ISBN 10 0761920846
In: Sociological methods and research, Band 39, Heft 1, S. 112-114
ISSN: 1552-8294
Time Series Analysis of Political Change
In: Handbooks of Sociology and Social Research; Handbook of Politics, S. 637-651
Introduction to the Special Issue on Model Selection
In: Sociological methods and research, Band 33, Heft 2, S. 167-187
ISSN: 1552-8294
PUBLIC OPINION RESEARCH AND POLITICAL SOCIOLOGY
In: Research in Political Sociology; Political Sociology for the 21st Century, S. 49-80
The Effects of Education on Political Opinions: An International Study
In: International journal of public opinion research, Band 14, Heft 2, S. 141-157
ISSN: 0954-2892
Research has found that education is associated with more liberal opinions on a number of issues, but there is uncertainty about the scope & interpretation of these findings. This study investigates the effects of education using data from the 1990 World Values Survey, which includes 40 nations & covers a wide range of opinions. Multilevel models are used to allow for national variation in the effects of education, including interactions with economic development & Communist rule. Education influences most political opinions; the effects can be summarized by saying that it promotes individualist values. Education is associated with somewhat lower confidence in most institutions. The relationship between education & confidence becomes weaker with economic development, while the effects of education on a number of political views shift to the left with economic development. The results suggest that education deserves more attention in explanations of national differences & historical trends in opinion. 2 Tables, 1 Figure, 32 References. Adapted from the source document.
A new populism? The case of Patrick Buchanan
In: Electoral Studies, Band 20, Heft 3, S. 447-461
A new populism? The case of Patrick Buchanan
In: Electoral studies: an international journal, Band 20, Heft 3, S. 447-462
ISSN: 0261-3794
Social Class and Voting: The Case against Decline
Debate surrounding the alleged decline of the influence of social class on voting behavior across the late-19th & 20th centuries is reviewed, & new evidence is presented to argue that class position continues to affect voting choices. Using individual-level data from the 1972-1994 General Social Surveys, class voting in the US is analyzed across three key sociodemographic factors: race, religious affiliation, & gender. The influence of other factors such as ideology, values, public opinion, birth cohort, material satisfaction, & party affiliation is also considered. Results indicate that such non-class-based attitudes & identities may override class divisions in voting; however, they do not do so consistently, & the influence of class sometimes coexists with these factors. 3 Tables, 2 Figures, 43 References. K. Hyatt Stewart
Social Class and Voting: The Case against Decline
Debate surrounding the alleged decline of the influence of social class on voting behavior across the late-19th & 20th centuries is reviewed, & new evidence is presented to argue that class position continues to affect voting choices. Using individual-level data from the 1972-1994 General Social Surveys, class voting in the US is analyzed across three key sociodemographic factors: race, religious affiliation, & gender. The influence of other factors such as ideology, values, public opinion, birth cohort, material satisfaction, & party affiliation is also considered. Results indicate that such non-class-based attitudes & identities may override class divisions in voting; however, they do not do so consistently, & the influence of class sometimes coexists with these factors. 3 Tables, 2 Figures, 43 References. K. Hyatt Stewart
A Critique of the Bayesian Information Criterion for Model Selection
In: Sociological methods and research, Band 27, Heft 3, S. 359-397
ISSN: 1552-8294
The Bayesian information criterion (BIC) has become a popular criterion for model selection in recent years. The BIC is intended to provide a measure of the weight of evidence favoring one model over another, or Bayes factor. It has, however, some important drawbacks that are not widely recognized. First, Bayes factors depend on prior beliefs about the expected distribution of parameter values, and there is no guarantee that the Bayes factor implied by the BIC will be close to one calculated from a prior distribution that an observer would actually regard as appropriate. Second, to obtain the Bayes factors that follow from the BIC, investigators would have to vary their prior distributions depending on the marginal distributions of the variables and the nature of the hypothesis. Such variations seem unwarranted in principle and tend to make the BIC inclined to favor excessively simple models in practice. These points are illustrated by the analysis of several examples, and alternatives to use of the BIC are discussed.