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2: Data and Methods
Pages 15-28

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From page 15...
... Since the current study panel was charged with examining career outcomes for Ph.D.s only in science and engineering, we examined five broad fields: • Mathematical Sciences: Mathematics, computer science, probability and statistics (including biometrics and biostatistics, psychometrics, econometrics, and social statistics) , and other fields of mathematics.
From page 16...
... • Life Sciences: Agriculture, biological sciences, and medical sciences. • Social and Behavioral Sciences: Anthropology, economics, geography, political science, psychology, sociology, and other social and behavioral sciences.
From page 17...
... . For a given year, the SDR provides demographic characteristics and the current employment status of those with doctoral degrees awarded between 1930 and the present.
From page 18...
... and employing program were matched with the 1973, 1979, and 1989 SDR data; the 1995 quality ratings were used for the 1995 employing program and for individuals who received their Ph.D.s between 1989 and 1994. YEAR OF SURVEY, YEAR OF PH.D., CAREER YEAR, AND SYNTHETIC COHORTS For each year of the SDR, data were analyzed for those with degrees from 1949 until the year of the survey.
From page 19...
... This design also allows us to compare the career outcomes of individuals who had the same career ages in different calendar years. For example: • Table 2-1 shows that the 1959 cohort was 20 years from their Ph.D.
From page 20...
... Chapter 4 shows that female doctoral scientists are less likely than men to be in the fulltime labor force. Women who are not working full time are excluded from Chapter 5, where gender differences in sector of employment and primary activity are examined.
From page 21...
... Production • Doctoral Degree Attainment. How has the percentage of doctoral degrees received by women changed since 1973?
From page 22...
... These variables include: Basic Control Variables • Field. Is the doctoral degree in engineering, mathematics, physical science, life science, or the social and behavioral sciences?
From page 23...
... We consider medical institutions to be Research I institutions except for some analyses of the life sciences. • Engineering institutions include schools of engineering.
From page 24...
... For example, a university that barely meets the requirements to be a Research I university may be very similar to institutions at the upper range of Research II universities. Second, the Carnegie classifications was revised in 1976, 1987, and 1994 (Carnegie Foundation for the Advancement of Teaching 1973, 1976, 1987, 1994)
From page 25...
... study was based on a matched sample. This involved constructing triads of two men and one woman that matched as nearly as possible on selected background characteristics, such as education and years of experience.
From page 26...
... The regressions are not used as causal models; rather they are sophisticated descriptions of the association between background characteristics and career outcomes. For example, if women with children are more likely to leave science, this is not conclusive evidence that the cause of these women leaving science is having children.
From page 27...
... The logit model specifies a nonlinear relationship between the probability that some event occurs and a set of independent variables. To interpret the effect of an independent variable, we compute the change in the predicted probability of some outcome when one of the independent variables changes by a given amount.
From page 28...
... The problem in presenting results from the logit model is that the expected change in the probability for a unit change in a variable differs depending on the current level of all variables in the model. To summarize the effect of a variable, we examined how a unit change in a variable affected the outcome probability when all variables were held constant, usually at their mean.


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