W. Holmes Finch

Ken Kelley

Jocelyn E. Bolin

A powerful tool for analyzing nested designs in a variety of fields, multilevel/hierarchical modeling allows researchers to account for data collected at multiple levels. Multilevel Modeling Using R provides you with a helpful guide to conducting multilevel data modeling using the R software environment.After reviewing standard linear models, the a

Multilevel Modeling Using R

Daniel Reardon

Anita G. Welch

Jocelyn H. Bolin

At a time when higher education institutions in the United States are the subject of increased media scrutiny and nearly continuous loss of funding by resource-strapped state legislatures, a greater understanding of higher education's bulwark resource--mid-career research and teaching faculty--is more important than ever. Faculty at mid-career comprise the largest segment of academia. For some, this is a time of significant productivity and creativity, yet for others, it is a time of disillusionment and stagnation. Revealing impediments and pathways to faculty job satisfaction and productivity will strengthen higher education institutions by protecting, fostering, and maintaining this vital workforce. In this collection we will explore the lives of mid-career faculty as our authors uncover the complexities in this stage of professional life and discuss support systems for the transition into this period of faculties' academic careers.Mid-Career Faculty: Trends, Barriers, and Possibilitiesis designed for faculty leaders, administration, policymakers, and anyone concerned with the future of higher education. This text offers an examination into an often overlooked period of academic life, that of post-tenure mid-career faculty. Therefore, the aim of this text is to deepen our understanding of the lives of mid-career faculty, to identify barriers that impede job advancement and satisfaction, and to offer suggestions for changes to current policy and practice in higher education.Contributors are: Joyce Alexander, Michael Bernard-Donals, Pradeep Bhardwaj, Kimberly Buch, Javier Cavazos, Jay R. Dee, Anne M. DeFelippo, Andrea Dulin, Jeremiah Fisk, Carrie Graham, Debbie L. Hahs-Vaughn, Florencio Eloy Hernandez, Yvette Huet, Jane McLeod, Jennifer McGarry, Maria L. Morales, Eliza Pavalko, Laura Plummer, Mandy Rispoli, Amanda J. Rockinson-Szapkiw, J. Blake Scott, Michael Terwillegar, Jenna Thomas and Claudia Vela.

Trends, Barriers, and Possibilities

Mid-career Faculty

Regression Analysis in R: A Comprehensive View for the Social Sciences covers the basic applications of multiple linear regression all the way through to more complex regression applications and extensions. Written for graduate level students of social science disciplines this book walks readers through bivariate correlation giving them a solid framework from which to expand into more complicated regression models. Concepts are demonstrated using R software and real data examples. Key Features: Full output examples complete with interpretation Full syntax examples to help teach R code Appendix explaining basic R functions Methods for multilevel data that are often included in basic regression texts End of Chapter Comprehension Exercises

Jocelyn E. Bolin

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