1.

Record Nr.

UNINA9910462038403321

Titolo

Multilevel modeling techniques and applications in institutional research [[electronic resource] /] / Joe L. Lott, II, James S. Antony, editors

Pubbl/distr/stampa

San Francisco, : Jossey-Bass, 2012

ISBN

1-118-45734-X

1-280-79294-9

9786613703330

1-118-45733-1

Descrizione fisica

1 online resource (144 p.)

Collana

New directions for institutional research, , 0271-0579 ; ; no. 154, summer 2012

Altri autori (Persone)

LottJoe L

AntonyJames S

Disciplina

370.72

378.0072

Soggetti

Social sciences - Mathematical models

Social sciences - Research - Mathematical models

Electronic books.

Lingua di pubblicazione

Inglese

Formato

Materiale a stampa

Livello bibliografico

Monografia

Note generali

Description based upon print version of record.

Nota di bibliografia

Includes bibliographical references and index.

Nota di contenuto

Multilevel Modeling Techniques and Applications in Institutional Research; Contents; Editors' Notes; 1: Hierarchical Data Structures, Institutional Research, and Multilevel Modeling; 2: Introduction to Estimation Issues in Multilevel Modeling; 3: Using Existing Data Sources/Programs and Multilevel Modeling Techniques for Questions in Institutional Research; 4: Multilevel Models for Binary Data; 5: Cross-Classified Random Effects Models in Institutional Research; 6: Multilevel Modeling: Applications to Research on the Assessment of Student Learning, Engagement, and Developmental Outcomes

7: Multilevel Modeling: Presenting and Publishing the Results for Internal and External Constituents INDEX

Sommario/riassunto

Multilevel modeling is an increasingly popular multivariate technique that is widely applied in the social sciences. Increasingly, practitioners are making instructional decisions based on results from their



multivariate analyses, which often come from nested data that lend themselves to multilevel modeling techniques. As data-driven decision making becomes more critical to colleges and universities, multilevel modeling is a tool that will lead to more efficient estimates and enhance understanding of complex relationships.  This volume illustrates both the theoretical underpinnings and