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By Mary B. Breckenridge

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Extra info for Age, Time, and Fertility. Applications of Exploratory Data Analysis

Sample text

00. The relative compactness of the range of rates at age cuts 19/20 and 24/25, and also at age cut 29/30 except for a few large outliers, directs attention to the role of age groups 3 0 - 3 4 and 3 5 - 3 9 in determining period differences in total fertility rates in this time sequence. Normalized Rates If w e are interested not only in fertility rates by age but also in the age pattern of fertility, our first step of dissection should be to normalize the cumulative rates. That is, the cumulative fertility rate at each of the seven age cuts in a period is divided by the rate at age cut 49/ 50, giving the proportion of total fertility in each period that can be attributed to w o m e n a given age and younger, as shown in the accompanying tabulation.

4. Total fertility rate is 5 2]=ifi(aj) in this case because w e are using rates for 5-year age groups. 5. A related procedure, trimmed mean polish, w a s used by Page (1977) in her investigation of the effects o f marriage duration o n marital fertility patterns. Instead of the median, the mean of the central two-thirds of a distribution w a s used in the s u c c e s s i v e approximations (see N o t e 6). 6. The E H R procedures also differ from these "polishing" procedures in another important regard—the weighting of the residuals in the iterative fitting procedure.

Which aggregations of data may obscure valuable information and which are less apt to do so? Will frequency distributions or cumulative distributions suit our purposes better? The exploration begins without detailed assumptions about the data or the patterns that underlie its variability. The analysis develops an increasingly complete description of the patterns by repeatedly removing regularities from the data (often starting by removing the median) and then looking at what is left over (the residuals).

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