Analyzing multilevel data: comparing findings from hierarchical linear modeling and ordinary least squares regression

This study examined the differing conclusions one may come to depending upon the type of analysis chosen, hierarchical linear modeling or ordinary least squares (OLS) regression. To illustrate this point, this study examined the influences of seniors' self-reported critical thinking abilities t...

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Published inHigher education Vol. 66; no. 4; pp. 439 - 461
Main Author Rocconi, Louis M.
Format Journal Article
LanguageEnglish
Published Dordrecht Springer 01.10.2013
Springer Netherlands
Springer Nature B.V
Subjects
Online AccessGet full text
ISSN0018-1560
1573-174X
DOI10.1007/s10734-013-9615-y

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Abstract This study examined the differing conclusions one may come to depending upon the type of analysis chosen, hierarchical linear modeling or ordinary least squares (OLS) regression. To illustrate this point, this study examined the influences of seniors' self-reported critical thinking abilities three ways: (1) an OLS regression with the student as the unit of analysis, (2) an OLS regression with the institution as the unit of analysis, and (3) a three-level hierarchical linear model. Overall, results demonstrate that one would come to substantively different conclusions regarding the influences on students' perceived critical thinking ability depending upon the type of analysis chosen, especially in regards to the effects of the institutional characteristics.
AbstractList This study examined the differing conclusions one may come to depending upon the type of analysis chosen, hierarchical linear modeling or ordinary least squares (OLS) regression. To illustrate this point, this study examined the influences of seniors' self-reported critical thinking abilities three ways: (1) an OLS regression with the student as the unit of analysis, (2) an OLS regression with the institution as the unit of analysis, and (3) a three-level hierarchical linear model. Overall, results demonstrate that one would come to substantively different conclusions regarding the influences on students' perceived critical thinking ability depending upon the type of analysis chosen, especially in regards to the effects of the institutional characteristics.[PUBLICATION ABSTRACT]
This study examined the differing conclusions one may come to depending upon the type of analysis chosen, hierarchical linear modeling or ordinary least squares (OLS) regression. To illustrate this point, this study examined the influences of seniors' self-reported critical thinking abilities three ways: (1) an OLS regression with the student as the unit of analysis, (2) an OLS regression with the institution as the unit of analysis, and (3) a three-level hierarchical linear model. Overall, results demonstrate that one would come to substantively different conclusions regarding the influences on students' perceived critical thinking ability depending upon the type of analysis chosen, especially in regards to the effects of the institutional characteristics. Keywords Hierarchical linear modeling * Ordinary least squares regression * Methodology * Critical thinking
This study examined the differing conclusions one may come to depending upon the type of analysis chosen, hierarchical linear modeling or ordinary least squares (OLS) regression. To illustrate this point, this study examined the influences of seniors' self-reported critical thinking abilities three ways: (1) an OLS regression with the student as the unit of analysis, (2) an OLS regression with the institution as the unit of analysis, and (3) a three-level hierarchical linear model. Overall, results demonstrate that one would come to substantively different conclusions regarding the influences on students' perceived critical thinking ability depending upon the type of analysis chosen, especially in regards to the effects of the institutional characteristics.
This study examined the differing conclusions one may come to depending upon the type of analysis chosen, hierarchical linear modeling or ordinary least squares (OLS) regression. To illustrate this point, this study examined the influences of seniors' self-reported critical thinking abilities three ways: (1) an OLS regression with the student as the unit of analysis, (2) an OLS regression with the institution as the unit of analysis, and (3) a three-level hierarchical linear model. Overall, results demonstrate that one would come to substantively different conclusions regarding the influences on students' perceived critical thinking ability depending upon the type of analysis chosen, especially in regards to the effects of the institutional characteristics. Reprinted by permission of Springer
This study examined the differing conclusions one may come to depending upon the type of analysis chosen, hierarchical linear modeling or ordinary least squares (OLS) regression. To illustrate this point, this study examined the influences of seniors' self-reported critical thinking abilities three ways: (1) an OLS regression with the student as the unit of analysis, (2) an OLS regression with the institution as the unit of analysis, and (3) a three-level hierarchical linear model. Overall, results demonstrate that one would come to substantively different conclusions regarding the influences on students' perceived critical thinking ability depending upon the type of analysis chosen, especially in regards to the effects of the institutional characteristics. Adapted from the source document.
Audience Higher Education
Postsecondary Education
Academic
Author Rocconi, Louis M.
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CitedBy_id crossref_primary_10_1007_s41959_023_00101_6
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Snippet This study examined the differing conclusions one may come to depending upon the type of analysis chosen, hierarchical linear modeling or ordinary least...
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eric
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springer
jstor
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StartPage 439
SubjectTerms Ability
Academic achievement
Analysis
Bias
College Seniors
College students
Colleges
Critical Thinking
Data Analysis
Education
Education, Secondary
Educational policy
Educational research
Extracurricular activities
Hierarchical Linear Modeling
Hierarchical scales
Hierarchies
Higher Education
Influences
Institutional Characteristics
Learning
Least squares method
Least Squares Statistics
Linear analysis
Linear equations
Linear models
Methodology
Methods
Modeling
Multilevel analysis
Multilevel models
Older people
Perception
Regression (Statistics)
Regression analysis
School campuses
Secondary Education
Standard error
Statistical methods
Statistical variance
Student Development
Students
Variables
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  priority: 102
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Title Analyzing multilevel data: comparing findings from hierarchical linear modeling and ordinary least squares regression
URI https://www.jstor.org/stable/43648501
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