Ed230C Experiment #5 - Analysis of Covariance

Using the Supplemental Math Instruction dataset or a dataset of your own choosing (with approval of the instructor). The Supplemental Math Instruction dataset is available as a stata file (suppmath.dta) and can be accessed using the Stata command:

use http://www.gseis.ucla.edu/courses/data/suppmath

If you use the Supplemental Math Instruction data, select math_score as the dependent variable and read_ability as the covariate. Explore the effects of the different levels of type and location using a completely randomized factorial analysis of covariance design. Your report of the data analysis should be written in the style of a technical report, that is, the write-up should be heavily concerned with the substantive meaning of the results. The report should include the following points:

1. Briefly describe the study, and the reason for investigating the variables you have chosen.

2. List the assumptions underlying the analysis of covariance and present evidence concerning how well the data in this experiments met these assumptions.

3. Perform the analysis of covariance. Provide the necessary tables and figures to report your results and to support the conclusions that you draw. In your analysis, be sure to examine heterogeneity of regression slopes as well as overall significance of each of your qualitative and quantitative predictors.

4. Compare the results of the analysis of covariance to an analysis without the covariate. What are the differences?

5. Attach annotated printouts showing that you understand and have examined the entire output.

6. Discuss the results and draw conclusions about the basic questions you set out to answer. Discuss the meaning (both statistical and practical) of your results.

Linear Statistical Models Course