By Mary B. Breckenridge
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Additional info for Age, Time, and Fertility. Applications of Exploratory Data Analysis
72 for those aged 2 5 - 2 9 . 05 by 1959. Sweden's experience in the 1950s, similar to that of other Northern and Western European countries, involved a much less pronounced "baby b o o m , " however, than occurred in the U . S . , Canada, Australia, and N e w Zealand (Teitelbaum, 1973; Campbell, 1974). The differences between the U . S . and Sweden, measured in the total fertility rates for the 1945-1965 period, can be examined in Fig. 1. Since that period, the low fertility rates in Sweden occur in a new context: the proportions of w o m e n married at the younger ages have returned to the levels of the 1930s, but the increasing popularity of nonmarital cohabitation has contributed to an unprecendented increase in the proportion of births that occur outside of legal marriage.
4 births per woman lasts for almost 30 cohorts. The earliest evidence of fertility limitation (or a consistent increase in fertility limitation) within marriage is usually associated with the cohorts of w o m e n w h o reached childbearing ages about 1865 (Hofsten and Lundstrom, 1976). These cohorts initiated the gradual but sustained decline in total rate, which became more pronounced with the cohorts aged 15 about 1890. 8 for the cohorts aged 15 in the period 1917-1921. Subsequent cohorts provide an example of marked variation in the timing of childbearing with little change in the level of cohort completed fertility.
By bringing under consideration the 85 years of little-analyzed pre-1860 data from "Grunddragen," this long sequence of single-year schedules also directs our attention to one of the strengths of the selected analytic approach—the detection of underlying patterns, even in flawed data. Single-year-of-age cohort overall fertility data, beginning with the birth cohort of 1870, and eight decades of detailed marital fertility data enrich the possibilities for cross-sequence comparisons. The second section of the chapter presents the philosophy and some of the tools of E D A in enough detail that the reader should be able to visualize their application to other data sets.