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A Partial Simulation Study of Phantom Effects in Multilevel Analysis of School Effects: The Case of School Socioeconomic Composition:

Hao Zhou, +1 more
- 01 Feb 2021 - 
- pp 004912412098619
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TLDR
This paper used hierarchical linear modeling (HLM) to estimate the effects of socioeconomic status (SES) on academic achievement at different levels of an educational system and found that if a prior acad...
Abstract
Hierarchical linear modeling (HLM) is often used to estimate the effects of socioeconomic status (SES) on academic achievement at different levels of an educational system. However, if a prior acad...

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A PARTIAL SIMULATION STUDY OF PHANTOM EFFECTS IN MULTILEVEL
ANALYSIS OF SCHOOL EFFECTS: THE CASE OF SCHOOL SOCIOECONOMIC
COMPOSITION
________________________________________
DISSERTATION
________________________________________
A dissertation submitted in partial fulfillment of the
requirements for the degree of Doctor of Philosophy in the
College of Education
at the University of Kentucky
By
Hao Zhou
Lexington, Kentucky
Director: Dr. Xin Ma, Professor of Quantitative and Psychometric Methods
Lexington, Kentucky
2019
Copyright © Hao Zhou 2019

ABSTRACT OF DISSERTATION
A PARTIAL SIMULATION STUDY OF PHANTOM EFFECTS IN MULTILEVEL
ANALYSIS OF SCHOOL EFFECTS: THE CASE OF SCHOOL SOCIOECONOMIC
COMPOSITION
Socioeconomic status (SES) affects students’ academic achievement at different
levels of an educational system. However, misspecified Hierarchical Linear Model (HLM)
may bias school SES estimation. In this study, a partial simulation study was conducted
to examine how misspecified HLM model bias school and student SES estimation.
The result of this study can be summarized by four important points. First, based
on partial simulation procedure, phantom effects of school SES and student SES are real.
Second, characteristics of phantom effects are generalized. The stronger the correlation
between prior science achievement measure and present science achievement measure,
the greater the decrease in both student SES effects and school SES effects. Third, the
procedure of partial simulation provides a new angle to conduct theoretical studies (full
simulation), which is entirely based on ideal assumption. Finally, the procedure of partial
simulation offers researchers a way to create prior student academic achievement
measures when they are not available for data analysis.
KEYWORDS: Partial Simulation Study, School SES Effect, Student SES Effect
Hao Zhou
(Name of Student)
04/26/2019
Date

A PARTIAL SIMULATION STUDY OF PHANTOM EFFECTS IN MULTILEVEL
ANALYSIS OF SCHOOL EFFECTS: THE CASE OF SCHOOL SOCIOECONOMIC
COMPOSITION
By
Hao Zhou
Dr. Xin Ma
Director of Dissertation
Dr. Margaret Bausch
Director of Graduate Studies
04/26/2019
Date

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Inadequacies in the SES–Achievement model: Evidence from PISA and other studies

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School socioeconomic-background effects are generally small: a response to Sciffer, Perry, and McConney

TL;DR: This paper argued that school socioeconomic background compositional effects are important for both research and policy, and proposed a method to measure the compositional effect of SES compositional influence on educational outcomes.
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TL;DR: This paper found that disciplinary climate was more often associated with science dispositions (epistemology, enjoyment, interest, instrumental, self-efficacy activities) in U.S. science classrooms, but an emphasis on teaching support in Canadian science classrooms.
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Meta-analytical insights on school SES effects

TL;DR: This article used meta-analysis to synthesize findings involving 480 effect sizes from 97 studies (dated 2000-2020) to provide insights on associations between school socioeconomic status (SES) and student learning outcomes; schools' percentage of ethnic minority students and students' prior ability; and school processes in K-12 schools.
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How much is too much time spent on homework: an exploratory study based on a Bayesian multilevel piecewise model with a random change point

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- 09 May 2023 - 
TL;DR: This article applied multilevel piecewise linear regression with a random effects model under a Bayesian estimation framework to a total of 5,072 7th grade students in 35 schools to search for an optimum time in terms of the effect of homework time on student academic achievement.
References
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Book

Statistical Power Analysis for the Behavioral Sciences

TL;DR: The concepts of power analysis are discussed in this paper, where Chi-square Tests for Goodness of Fit and Contingency Tables, t-Test for Means, and Sign Test are used.
Book

Hierarchical Linear Models: Applications and Data Analysis Methods

TL;DR: The Logic of Hierarchical Linear Models (LMLM) as discussed by the authors is a general framework for estimating and hypothesis testing for hierarchical linear models, and it has been used in many applications.
Journal ArticleDOI

Hierarchical Linear Models: Applications and Data Analysis Methods.

TL;DR: This chapter discusses Hierarchical Linear Models in Applications, Applications in Organizational Research, and Applications in the Study of Individual Change Applications in Meta-Analysis and Other Cases Where Level-1 Variances are Known.
Journal ArticleDOI

Socioeconomic Status and Academic Achievement: A Meta-Analytic Review of Research

TL;DR: In this paper, a meta-analysis reviewed the literature on socioeconomic status and academic achievement in journal articles published between 1990 and 2000 and showed a medium to strong SES-achievement relation.
Journal ArticleDOI

The relation between socioeconomic status and academic achievement.

TL;DR: This article found that SES is only weakly correlated with academic achievement, and with aggregated units of analysis, typically obtained correlations between SES and academic achievement jump to.73.
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