71 research outputs found

    How Consistent Are Class Size Effects?

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    Evidence from Project STAR has suggested that on average small classes increase student achievement. However, thus far researchers have focused on computing mean differences in student achievement between smaller and larger classes. In this study I focus on the distribution of the small class effects at the school level and compute the inconsistency of the treatment effects across schools. I use data from Project STAR and estimated small class effects for each school on mathematics and reading scores from kindergarten through third grade. The results revealed that school-specific small class effects are both positive and negative and that although students benefit considerably from being in small classes in some schools, in other schools being in small classes is a disadvantage. Small class effects were inconsistent and varied significantly across schools. Full time teacher aide effects were also inconsistent across schools and in some schools students benefit considerably from being in regular classes with a full time aide, while in other schools being in these classes is a disadvantage.small classes, treatment variability, meta-analysis

    Incorporating Cost in Power Analysis for Three-Level Cluster Randomized Designs

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    In experimental designs with nested structures entire groups (such as schools) are often assigned to treatment conditions. Key aspects of the design in these cluster randomized experiments include knowledge of the intraclass correlation structure and the sample sizes necessary to achieve adequate power to detect the treatment effect. However, the units at each level of the hierarchy have a cost associated with them and thus researchers need to decide on sample sizes given a certain budget, when designing their studies. This paper provides methods for computing power within an optimal design framework (that incorporates costs of units in all three levels) for three-level cluster randomized balanced designs with two levels of nesting. The optimal sample sizes are a function of the variances at each level and the cost of each unit. Overall, larger effect sizes, smaller intraclass correlations at the second and third level, and lower cost of level-3 and level-2 units result in higher estimates of power.experimental design, statistical power, optimal sampling

    Fixed Effects and Variance Components Estimation in Three-Level Meta-Analysis

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    Meta-analytic methods have been widely applied to education, medicine, and the social sciences. Much of meta-analytic data are hierarchically structured since effect size estimates are nested within studies, and in turn studies can be nested within level-3 units such as laboratories or investigators, and so forth. Thus, multilevel models are a natural framework for analyzing meta-analytic data. This paper discusses the application of a Fisher scoring method in two- and three-level meta-analysis that takes into account random variation at the second and at the third levels. The usefulness of the model is demonstrated using data that provide information about school calendar types. SAS proc mixed and HLM can be used to compute the estimates of fixed effects and variance components.meta-analysis, multilevel models, random effects

    The Gender Gap Reloaded: Are School Characteristics Linked to Labor Market Performance?

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    This study examines the wage gender gap of young adults in the 1970s, 1980s, and 2000 in the US. Using quantile regression we estimate the gender gap across the entire wage distribution. We also study the importance of high school characteristics in predicting future labor market performance. We conduct analyses for three major racial/ethnic groups in the US: Whites, Blacks, and Hispanics, employing data from two rich longitudinal studies: NLS and NELS. Our results indicate that while some school characteristics are positive and significant predictors of future wages for Whites, they are less so for the two minority groups. We find significant wage gender disparities favoring men across all three surveys in the 1970s, 1980s, and 2000. The wage gender gap is more pronounced in higher paid jobs (90th quantile) for all groups, indicating the presence of a persistent and alarming "glass ceiling."Wages, gender differences, school effects, quantile regression

    Is the Persistence of Teacher Effects in Early Grades Larger for Lower-Performing Students?

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    We examined the persistence of teacher effects from grade to grade on lower-performing students using high-quality experimental data from Project STAR, where students and teachers were assigned randomly to classrooms of different sizes. The data included information about mathematics and reading scores and student demographics such as gender, race, and SES. Teacher effects were computed as residual classroom achievement within schools and within grades. Then, teacher effects were used as predictors of achievement in following grades and quantile regression was used to estimate their persistence. Results consistently indicated that all students benefited similarly from teachers. Overall, systematic differential teacher effects were not observed and it appears that lower-performing students benefit as much as other students from teachers. In fourth grade there was some evidence that lower-performing students benefit more from effective teachers. Results from longitudinal analyses suggested that having effective teachers in successive grades is beneficial to all students and to lower-performing students in particular in mathematics. However, having low-effective teachers in successive grades is detrimental to all students and to lower-performing students in particular in reading.quantile regression, low-achievers, teacher effects

    Constructing a More Powerful Test in Two-Level Block Randomized Designs

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    A more powerful test is proposed for the treatment effect in two-level block randomized designs where random assignment takes place at the first level. When clustering at the second level is assumed to be known, the proposed test produces higher estimates of power than the typical test

    How long do teacher effects persist?

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    Previous findings from experimental and non-experimental studies have demonstrated that teachers differ in their effectiveness. In addition, evidence from non-experimental studies has indicated that teacher effects can last up to five years. This study used high-quality data from a four-year randomized experiment in which teachers and students were randomly assigned to classes to examine whether teacher effects on student achievement persist over time. Teacher effects are defined as teacher specific residuals adjusted for student and treatment effects. Findings indicate that the teacher effects are cumulative and observed not only in the current or the following grade, but they endure up to three years in early elementary grades. The findings also suggest that teacher effects are important and their additive effects on student achievement are as large as the additive effects of small classes. Finally, teacher effects are larger in reading than in mathematics

    Trends of school effects on student achievement: evidence from NLS:72, HSB:82, and NELS:92

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    The impact of schools on student achievement has been of great interest for the last four decades. This study examines trends of school effects on student achievement employing three national probability samples of high school seniors: NLS:72, HSB:82, and NELS:92. Hierarchical linear models are used to investigate school effects. The findings reveal that the substantial proportion of the variation in student achievement lies within schools not between schools. There is also considerable between school variation in achievement, which becomes larger over time. Schools are more diverse and more segregated in the 1990s than in the 1970s. In addition, school characteristics such as school region, school SES, and certain characteristics of the student body of the school, such as students' daily attendance, students in college preparatory classes, and high school graduates enrolled in colleges are important predictors of average student achievement. The school predictors explained consistently more than 50% of the variation in average student achievement across surveys. We also find considerable teacher heterogeneity in achievement within schools, which suggests important teacher effects on student achievement. Teacher heterogeneity in student achievement was larger than school heterogeneity, which may indicate that teacher effects have a relatively larger impact on mathematics and science student achievement than school effects

    A comment on variance decomposition and nesting effects in two- and three-level designs

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    Multilevel models are widely used in education and social science research. However, the effects of omitting levels of the hierarchy on the variance decomposition and the clustering effects have not been well documented. This paper discusses how omitting one level in three-level models affects the variance decomposition and clustering in the resulting two-level models. Specifically, I used the ANOVA framework and provided results for simple models that do not include predictors and assumed balanced nested data (or designs). The results are useful for teacher and school effects research as well as for power analysis during the designing stage of a study. The usefulness of the methods is demonstrated using data from Project STAR
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