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Baltimore native Henry Louis Mencken (1880-1956) was an essayist, literary critic, magazine editor, novelist, and journalist. Starting as a reporter for the Baltimore Morning Herald at the turn of the century, Mencken eventually became associated with the Baltimore Sun and his work for the newspaper spanned five decades. In H.L. Mencken: An Annotated Bibliography, S.T. Joshi provides the most exhaustive and comprehensive bibliography of the writings of H. L. Mencken ever assembled. It presents detailed information on his book publications from 1903 to the present, with a full list of editions and reprints. Most significantly, it presents for the first time a comprehensive annotated listing of his magazine and newspaper work (including more than 1,500 anonymous editorials for the Baltimore Sun, Baltimore Evening Sun, and other papers, which have never been listed in any previous bibliographies), a thorough index to his book reviews, and a full list of interviews Mencken gave during his lifetime. Word counts of nearly every item in the bibliography have been supplied, and the book has been thoroughly indexed by name, title, and periodical. Because every item has been annotated, scholars and students can, for the first time, gain an idea of the subject-matter of all Mencken's writings, especially his magazine and newspaper work. The indexes will allow users to locate any given item with ease. The chronological arrangement of each section allows users to understand the growth and development of Mencken's work, making this volume an invaluable resource.

(sponsored by the Educational Statisticians, SIG) Multilevel Modeling of Educational Data, co-edited by Ann A. O’Connell, Ed.D., and D. Betsy McCoach, Ph.D., is the next volume in the series: Quantitative Methods in Education and the Behavioral Sciences: Issues, Research and Teaching (Information Age Publishing), sponsored by the Educational Statisticians' Special Interest Group (Ed-Stat SIG) of the American Educational Research Association. The use of multilevel analyses to examine effects of groups or contexts on individual outcomes has burgeoned over the past few decades. Multilevel modeling techniques allow educational researchers to more appropriately model data that occur within multiple hierarchies (i.e.- the classroom, the school, and/or the district). Examples of multilevel research problems involving schools include establishing trajectories of academic achievement for children within diverse classrooms or schools or studying school-level characteristics on the incidence of bullying. Multilevel models provide an improvement over traditional single-level approaches to working with clustered or hierarchical data; however, multilevel data present complex and interesting methodological challenges for the applied education research community. In keeping with the pedagogical focus for this book series, the papers this volume emphasize applications of multilevel models using educational data, with chapter topics ranging from basic to advanced. This book represents a comprehensive and instructional resource text on multilevel modeling for quantitative researchers who plan to use multilevel techniques in their work, as well as for professors and students of quantitative methods courses focusing on multilevel analysis. Through the contributions of experienced researchers and teachers of multilevel modeling, this volume provides an accessible and practical treatment of methods appropriate for use in a first and/or second course in multilevel analysis. A supporting website links chapter examples to actual data, creating an opportunity for readers to reinforce their knowledge through hands-on data analysis. This book serves as a guide for designing multilevel studies and applying multilevel modeling techniques in educational and behavioral research, thus contributing to a better understanding of and solution for the challenges posed by multilevel systems and data.

Simplifying the often confusing array of software programs for fitting linear mixed models (LMMs), Linear Mixed Models: A Practical Guide Using Statistical Software provides a basic introduction to primary concepts, notation, software implementation, model interpretation, and visualization of clustered and longitudinal data. This easy-to-nav