Selecting statistical procedures for multi-level data : examining relationships between principal authenticity and teacher trust and engagement

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Wang, C., & Bird, J. (2011). Selecting statistical procedures for multi-level data : examining relationships between principal authenticity and teacher trust and engagement. Ceme Technical Report.
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Description

Faculty, It is a common practice in educational research to model treatment variables at the classroom level rather than at the student level. Students are naturally nested within classrooms in the educational system; therefore, randomly assigning students at the student level into treatment and control groups is often not practical. Data collected in educational settings are usually hierarchical in nature, for example, students nested within classrooms and classrooms nested within schools. Failure to consider the hierarchical structure of educational data could cause unreliable estimation of the effectiveness of school context or teacher quality on student learning outcomes and could misdirect educational policies and practices (Raudenbush and Bryk, 2002). Three major concerns should be taken into consideration when analyzing multi-level data: (a) unit of analysis, (b) statistical procedures, and (c) conceptual fallacy.

Details
Title

Selecting statistical procedures for multi-level data : examining relationships between principal authenticity and teacher trust and engagement

Author(s)

Wang, Chuang
Bird, Jim

UNC Charlotte Affiliate Type

Faculty

Extent

1 online resource

Date Published

2011

Genre

technical reports

Resource Type

text

Abstract

It is a common practice in educational research to model treatment variables at the classroom level rather than at the student level. Students are naturally nested within classrooms in the educational system; therefore, randomly assigning students at the student level into treatment and control groups is often not practical. Data collected in educational settings are usually hierarchical in nature, for example, students nested within classrooms and classrooms nested within schools. Failure to consider the hierarchical structure of educational data could cause unreliable estimation of the effectiveness of school context or teacher quality on student learning outcomes and could misdirect educational policies and practices (Raudenbush and Bryk, 2002). Three major concerns should be taken into consideration when analyzing multi-level data: (a) unit of analysis, (b) statistical procedures, and (c) conceptual fallacy.

Subjects--Topics

Educational evaluation
Quantitative research

Is Part Of

CEME technical report

Language

English

Publisher's Version

http://ceme.charlotte.edu/sites/ceme.charlotte.edu/files/media/pdfs/CEME...

Permalink

http://hdl.handle.net/20.500.13093/work:810

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