The strength of a multi-level analysis is its ability to analyze how higher levels of variables mediate the relationship between lower levels of variables. Thus, Hypothesis II is as follows: the more 'supportive' a community college is toward vocational education (along the lines described above for Hypothesis I), the smaller the race, gender, and SES gap in wages and use of training on the job."
8. Is the specific research design identified and described.
The research design is identified and discussed in great length, including identification of the independent and dependent variables. The dependent variables were wages and use of training student; and the independent variables were identified as: enrollment size, faculty (part-time/full-time), vocational emphasis, and availability of student services. The researcher used student transcripts and GPAs to construct the variables. Gender and race were not included on the list of independent variables, however these demographic factors were incorporated in data analysis.
9. Who were the subjects, how were they obtained?
The subjects consisted of a national sample of community college students who had earned at least 30 credit hours at a community college. The author arrived at this number based on previous research by Kane and Rouse (1993). The sample did not include any students who had attended a four-year college.
10. What methods were used to collect data, and analysis data? What strategies were used to ensure validity and reliability?
The author used two sets of basic hierarchical models designed to analyze the relationships within and between student-level and community college-level outcomes. Validity and reliability were not discussed.
11.What measures did they use?
According to the author, "These...
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