power considerations for educational studies with restricted samples that use state tests as pretest...
TRANSCRIPT
Power Considerations for Educational Studies with Restricted Samples that Use
State Tests as Pretest and Outcome Measures
June 2010
Presentation at the Institute for Education Sciences Research Conference
Russell Cole ● Josh Haimson ● Irma Perez-Johnson ● Henry May
The research reported here was supported by the National Center for Education Evaluation and Regional Assistance, U.S. Department of Education, through contract ED-04-CO-0112 to Mathematica Policy Research.
Randomized controlled trial (RCT)– Unbiased estimate of program impact– Increasingly prevalent in education research
Probability of detecting a true program impact is based on n, , effect size (ES)– Use of pretest can increase power (1-– Pretest-Posttest correlation shrinks minimum
detectable effect size (MDES)
Measuring impact of education intervention
3
2(1 )* * *(1 )A
n kRMDES M n P P
2 2
,( )A Post PreR r
State assessments as outcomes– Used to define proficiency for AYP
– Universal in grades 3–8 (Math and ELA)
– Minimizes burden
– Low(er) cost and scale scores readily available
State tests tend to have lower CSEM at middle of ability distribution– Largest CSEM at tails
– Variance (2) can be partitioned into explainable and unexplainable (measurement error) components
– Given increased CSEM at tails, samples of students selected at tails will have higher proportions of unexplainable variance
State Tests Prevalent, But Appropriate?
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If there is greater measurement error for low-performing students, does this mean that pretest-posttest correlations will be attenuated?
To capture variability in correlation coefficients associated to measurement error, select samples with different average achievement levels and calculate r
Compare pretest-posttest correlations across different achievement levels (and across states) to inform power calculations
General Methodology
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(i.e. )Pre,Post|Prer
Research Questions
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What is the average pretest-posttest correlation coefficient for samples of students selected at different pretest achievement levels?
Do correlation coefficients differ by state?
4 complete states + 2 large districts from 2 additional states
3 years of population data – 2 sets of pre-post correlations – (Year1,Year2), (Year2,Year3)
English/Language Arts & Mathematics
Grades 3–8
Population Data
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1. Sample pretest achievement level determinedA. Lowest performers
B. Proficiency threshold
C. Average performers
2. Grade grouping (pretest year)A. Early elementary (grades 3 and 4)
B. Late elementary (grade 5)
C. Middle school (grades 6 and 7)
Analysis Decisions
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For each state, year, subject, and grade-group:
1. Pretest standardization
2. Selection of study samples (n = 500)
3. Calculation of pretest-posttest correlation
– 6 states, 2 years pre-post data, 2 subjects, 3 grade groups for each achievement level
4. Cross-cutting aggregation (ANOVA)
Analysis Procedure
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Pretest-posttest correlations – Large attenuation when homogeneous sample
selected– Might be lower than anticipated for low performers
on state assessments– Similar for ELA/Mathematics and across grade levels– Affected by other factors (ceiling/floor effects)
Use available administrative records to gauge
Discussion/Summary
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Pre,Post|Prer
Thank you
May, Henry, Irma Perez-Johnson, Joshua Haimson, Samina Sattar, and Phil Gleason (2009). “Using State Tests in Education
Experiments: A Discussion of the Issues.” (NCEE 2009-013). Washington, DC: National Center for Education Evaluation and
Regional Assistance, Institute of Education Sciences, U.S. Department of Education.
http://ies.ed.gov/ncee/pdf/2009013.pdf
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