Summarize the article “Prekindergarten Age-Cutoff Regression-Discontinuity Desig

Question

Summarize the article “Prekindergarten Age-Cutoff Regression-Discontinuity Design- Methodological Issues and Implications for Application” based on the 3 aspects specified below:

I was unable to attach the article. Will have to google.

1. Briefly discuss each of the potentially problematic features of the Age-Cutoff RDD in your own words.

2. What suggestions and/or recommendations have the authors provided to improve the age-cutoff RDD in your own words?

3. What was your overall evaluation (i.e., strengths and weaknesses) of the article?

Explanation / Answer

Question: Summarize the article “Prekindergarten Age-Cutoff Regression-Discontinuity Design- Methodological Issues and Implications for Application” based on the 3 aspects specified below:

I was unable to attach the article. Will have to google.

1. Briefly discuss each of the potentially problematic features of the Age-Cutoff RDD in your own words.

2. What suggestions and/or recommendations have the authors provided to improve the age-cutoff RDD in your own words?

3. What was your overall evaluation (i.e., strengths and weaknesses) of the article?

Answer: The existing research studing the causal effects of prekindergarten programs upon the school readiness have used regression-discontinuity design (RDD) with the age cutoff for selection and assignment to two experimental conditions of treatment and control group. RDD is thought to have strong internal validity if key assumptions are met and therefore studies seem to suggestive of effectiveness of such programs. However some technical design problems have been overlooked in this design which might lead to biased effect estimates. This article focus upon discussion of such problems, and suggest ways to improve the RDD design.

Due to the nature of design, age is cutting point that divides sample into two groups – treatment and control group. Due to the differences (discontinuity) of age in two groups there appears to be a discontinuity in regression line. The authors explain that the problem due to age related cut-off in groups become unequal in the beginning and thus internal validity of there comparison become questionable. The control and treatment groups might differ due to other variables like differences due to maturity (outside the experimental - like maturity

To overcome this issue the researchers suggest to accommodate age factor into the model by taking two cohorts and assigning them to two conditions as below

Take baseline data from first and second cohort in first year one cohort with pre-k and second one with no pre-k

In the next year again test the first cohort without treatment an second cohort with treatment condition.

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