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Demystifying the Regression Coefficient: Rethinking Demystifying the Regression Coefficient: Rethinking

Demystifying the Regression Coefficient: Rethinking - PowerPoint Presentation

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Demystifying the Regression Coefficient: Rethinking - PPT Presentation

a Complex T ool for Use in P olicy R esearch Jeffrey S Napierala Prof Glenn D Deane Department of Sociology SUNY Albany Prof Donald J Hernandez Department of Sociology Hunter College amp CUNY Graduate Center ID: 473570

reading approach research results

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Demystifying the Regression Coefficient: Rethinking a Complex Tool for Use in Policy Research

Jeffrey S. NapieralaProf. Glenn D. DeaneDepartment of Sociology, SUNY AlbanyProf. Donald J. HernandezDepartment of Sociology, Hunter College & CUNY Graduate Center

Research was supported by a Grant from the Annie E. Casey Foundation

Please do not cite or distribute this research without consent from the AuthorsSlide2

OutlineThe origins of this methodAn example using children's reading performanceA “hybrid” approachStandard ErrorsResultsConclusionsSlide3

OriginsThe audience for policy research often has a diverse background in statistics.To accommodate those without any proficiency, the presentation must be simple and transparent.To satisfy those with advanced proficiency, current methods must be used.We want to have our cake and eat it too…Slide4

OriginsAt one end of the spectrum: Sample means/proportions are simple and easy to understand …but may not clearly translate into effective policies…Towards the other end: A standard regression approach has obvious advantages, but results can be difficult to explain to general audiences.Slide5

Origins

Hernandez, Donald J

.

Double Jeopardy: How Third-Grade Reading Skills and Poverty

Influence

High School

Graduation

. Baltimore: Annie E. Casey FoundationSlide6

An Example…Policy Question: How much would income transfers increase the percentage of (3rd Grade) students reading at the proficient level? Data: National Longitudinal Survey of Youth (NLSY)

4,060 children in 2369 families followed across about 30 yearsDependent variable: Peabody Individual Achievement (PIAT) Reading Comprehension Test. Continuous variable ranging from 1-99.Methods: Weighted, linear GEE models with a correction for clustering within families.Slide7

An Example: Model SpecificationTwo models to highlight approach:1. A “Base” model with just income and income squared predicting PIAT Reading Comprehension.

2. A “Full” model with controls for the 1) non-linear effect of mother’s education, 2) health insurance coverage, 3) whether a child attended head start or preschool, 4) the “quality” of their neighborhood, 5) race, 6) sex

, and

7) year

of interview.Slide8

A “hybrid” ApproachLet’s utilize the power of a regression, but keep the presentation as simple and flexible as possible.Create a statistical model of the outcome.“Simulate” new outcomes using the relevant parameters of the model.

Meaningfully summarize the distributions before and after the “simulation” using simple statistics/tabulations.Compare the summary statistics/tabulations.Slide9

A “hybrid” Approach: Standard ErrorsUsing the common formula for the standard error of a proportion (with and without a Design Effect multiplier of 1.388).A Monte-Carlo approach to incorporate error from the sample regression and sample proportion.

First, the effect(s) of covariates are added into the original score (the raw DV) by sampling from a normal distribution with a mean and s.d. from the regression.Rates (of reading proficiency) are computed then additional sampling error is introduced.After 5000 iterations, the S.E. of the distribution is computed from all the rates.Slide10

Also, to compare rates from the same group of children (before and after “simulations”) a “paired proportions” t-test is used (Altman 1997).Source: Altman, Douglas G. 1997. Practical Statistics for Medical Research. London: Chapman & Hall.

A “hybrid” Approach: Standard ErrorsSlide11

Results…Slide12

Results…Slide13

Results…Slide14

Results…Slide15

Results…Slide16

Results…Slide17

ConclusionsThe “hybrid” approach has a few notable advantages over other methods…The independent effect of income on reading proficiency is much (much) less than might be expected from looking at bivariate or univariate results.We expect that about 4% (2.5-5.9; 95% C.I

.) more kids in poverty would read proficiently if their families were given additional income to move them out of povery.Slide18

Thank You!Email: jnapierala@albany.eduSlide19
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