We propose a remedy for the discrepancy between the way political scientists analyze data with missing values and the recommendations of the statistics community. Methodologists and statisticians agree that "multiple imputation" is a superior approach to the problem of missing data

www.people.cornell.edu/pages/edo1/.

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that the DP model is able to account for wide variety of phenomena observed in the data, including the pronounced peaks in the distribution of retirement ages at 62 and 65 (the ages of early and normal eligibility for Social Security benefits, respectively). We identify a significant fraction of “health

Nonlinear mixed effects models for data in the form of continuous, repeated measurements on each of a number of individuals, also known as hierarchical nonlinear models, are a popular platform for analysis when interest focuses on individual-specific characteristics. This framework first enjoyed

and for female youth were substantial. Beneficial effects for female youth on education, risky behavior, and physical health were offset by adverse effects for male youth. For outcomes exhibiting significant treatment effects, we find, using variation in treatment intensity across voucher types and cities

Stereotype research emphasizes systematic processes over seemingly arbitrary contents, but content also may prove systematic. On the basis of stereotypes ’ intergroup functions, the stereotype content model hypothesizes that (a) 2 primary dimensions are competence and warmth, (b) frequent mixed clusters combine high warmth with low competence (paternalistic) or high competence with low warmth (envious), and (c) distinct emotions (pity, envy, admiration, contempt) differentiate the 4 competence– warmth combinations. Stereotypically, (d) status predicts high competence, and competition predicts low warmth. Nine varied samples rated gender, ethnicity, race, class, age, and disability out-groups. Contrary to antipathy models, 2 dimensions mattered, and many stereotypes were mixed, either pitying (low competence, high warmth subordinates) or envying (high competence, low warmth competitors). Stereotypically, status predicted competence, and competition predicted low warmth. Not all stereotypes are alike. Some stereotyped groups are disrespected as incapable and useless (e.g., elderly people), whereas others are respected for excessive, threatening competence (e.g., Asians). Some stereotyped groups are liked as sweet and harmless (e.g., housewives), whereas others are disliked as cold and inhuman (e.g., rich people). Surely, such differences matter. However, social psychology of late has eschewed the study of stereotype content, focusing instead on stereotyping processes (for

, have produced a new generation of flexible procedures with a sound statistical basis. These procedures involve multiple imputation (Rubin, 1987), a simu-lation technique that replaces each missing datum with a set of m>1 plausible values. The m versions of the complete data are analyzed by standard

Document Version Preprint – the version submitted for publication Link to publication record in King's Research Portal Citation for published version (APA): Shea, N. (2011). Acquiring a new concept is not explicable-by-content. Behavioral and Brain Sciences, 34(3), 148-149doi: 10.1017/S0140525X10002219 Page numbers When referring to this paper, please check the page numbers in the published version and cite these. General rights Copyright and moral rights for the publications made accessible in the public portal are retained by the authors and/or other copyright owners and it is a condition of accessing publications that users recognise and abide by the legal requirements associated with these rights. • Users may download and print one copy of any publication from the public portal for the purpose of private study or research. • You may not further distribute the material or use it for any profit-making activity or commercial gain • You may freely distribute the URL identifying the publication in the public portal? Take down policy If you believe that this document breaches copyright please contact librarypure@kcl.ac.uk providing details, and we will remove access to the work immediately and investigate your claim.

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