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Demographic Research | Vol.28, Issue. | 2017-05-23 | Pages

Demographic Research

A Stata module for computing fertility rates and TFRs from birth histories: tfr2

Bruno Schoumaker  
Abstract

BACKGROUND Since the 1970s, birth history data have become widely available, thanks to the World Fertility survey and the Demographic and Health Surveys programs. Despite their wide availability, these data remain under-exploited. Computation, even of simple indicators (fertility rates, total fertility rates, mean age at childbearing) and their standard errors, is not direct with such data, and other types of analysis (fertility differentials, reconstruction of fertility trends et cetera) may also involve reorganization of data sets and statistical modeling that present a barrier to the use of birth history data. OBJECTIVE This paper presents a Stata software module (tfr2) that was prepared to analyze birth history data in a user-friendly and flexible way. It is designed to be used primarily with DHS data, but can also be used easily with birth histories from other sources. Three types of analysis are performed by tfr2: (1) the computation of age-specific fertility rates and TFRs, as well as their standard errors, (2) the reconstruction of fertility trends, and (3) the estimation of fertility differentials (rate ratios). METHODS The tfr2 module is composed of two parts: (1) a Stata command to transform birth history data into a table of births and exposure (tabexp), and (2) a Poisson regression model to compute fertility rates, fertility trends and fertility differentials from a table of births and exposure (produced by tabexp). COMMENTS One can obtain tfr2 free of charge. It will work with Stata 10 and more recent versions of Stata.

Original Text (This is the original text for your reference.)

A Stata module for computing fertility rates and TFRs from birth histories: tfr2

BACKGROUND Since the 1970s, birth history data have become widely available, thanks to the World Fertility survey and the Demographic and Health Surveys programs. Despite their wide availability, these data remain under-exploited. Computation, even of simple indicators (fertility rates, total fertility rates, mean age at childbearing) and their standard errors, is not direct with such data, and other types of analysis (fertility differentials, reconstruction of fertility trends et cetera) may also involve reorganization of data sets and statistical modeling that present a barrier to the use of birth history data. OBJECTIVE This paper presents a Stata software module (tfr2) that was prepared to analyze birth history data in a user-friendly and flexible way. It is designed to be used primarily with DHS data, but can also be used easily with birth histories from other sources. Three types of analysis are performed by tfr2: (1) the computation of age-specific fertility rates and TFRs, as well as their standard errors, (2) the reconstruction of fertility trends, and (3) the estimation of fertility differentials (rate ratios). METHODS The tfr2 module is composed of two parts: (1) a Stata command to transform birth history data into a table of births and exposure (tabexp), and (2) a Poisson regression model to compute fertility rates, fertility trends and fertility differentials from a table of births and exposure (produced by tabexp). COMMENTS One can obtain tfr2 free of charge. It will work with Stata 10 and more recent versions of Stata.

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Bruno Schoumaker,.A Stata module for computing fertility rates and TFRs from birth histories: tfr2. 28 (),.

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