A platform for research: civil engineering, architecture and urbanism
A platform for research: civil engineering, architecture and urbanism
Grouped zero-inflated count data models of coital frequency
Abstract. Various count data models are applied to data collected from a sample of Norfolk young persons, who were asked how many times they had had sexual intercourse during the previous two-week period. The models take account of the fact that the data are “grouped”, meaning that for some observations, the count is not known exactly but is known to fall in a particular range. Using a formal testing procedure, we find overwhelming evidence of the presence of excess zeros, and this we attribute to the fact that, at any time, a certain proportion of the population are sexually inactive. Our final model contains two equations, the first being the participation equation which determines whether an individual is sexually active, and the second being the frequency equation which determines the count, conditional on being active. Age, gender, salary, occupational status, marital status and type of living environment all have interesting effects on either participation or frequency. Since a significant proportion of the original sample declined to reveal coital frequency, we address the potential problem of selection bias by including a Heckman-type correction term during the model selection process.
Grouped zero-inflated count data models of coital frequency
Abstract. Various count data models are applied to data collected from a sample of Norfolk young persons, who were asked how many times they had had sexual intercourse during the previous two-week period. The models take account of the fact that the data are “grouped”, meaning that for some observations, the count is not known exactly but is known to fall in a particular range. Using a formal testing procedure, we find overwhelming evidence of the presence of excess zeros, and this we attribute to the fact that, at any time, a certain proportion of the population are sexually inactive. Our final model contains two equations, the first being the participation equation which determines whether an individual is sexually active, and the second being the frequency equation which determines the count, conditional on being active. Age, gender, salary, occupational status, marital status and type of living environment all have interesting effects on either participation or frequency. Since a significant proportion of the original sample declined to reveal coital frequency, we address the potential problem of selection bias by including a Heckman-type correction term during the model selection process.
Grouped zero-inflated count data models of coital frequency
Moffatt, Peter G. (author) / Peters, Simon A. (author)
2000
Article (Journal)
English
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