A Semiparametric Sequential Ordinal Model with Applications to Analyse First Birth Intervals
DOI:
https://doi.org/10.17713/ajs.v38i2.263Abstract
A semiparametric sequential ordinal model is proposed to analyze socio-demographic and spatial determinants of first birth intervals after marriage. Random effects are introduced to capture spatially structured and unstructured latent covariates. The structured effects are modelled by assuming conditional autoregressive priors, and for the unstructured effects we use an exchangeable Gaussian prior, while the smooth effects of continuous covariatesare modelled by penalized splines. Inference is based on the mixed model approach. The model is applied to data from a cross-sectional survey. Compared to a spatial parametric predictor, the spatial semiparametric model better fits the data.
References
Albert, J., and Chib, S. (1997). Bayesian methods for cumulative, sequential and twostep ordinal data regression models (Tech. Rep.). Department of Mathematics and Statistics, Bowling Green State University. (Preprint Series)
Albert, J., and Chib, S. (2001). Sequential ordinal modelling with applications to survival data. Biometrics, 57, 829-836.
Besag, J., York, J., and Mollie, A. (1991). Bayesian image restoration with two applications in spatial statistics (with discussion). Annals of the Institute of Statistical Mathematics, 43, 1-59.
Borgoni, R., and Billari, F. C. (2003). Bayesian spatial analysis of demographic survey data: An application to contraceptive use at first sexual intercourse. Demographic Research, 8, 3.
Brezger, A., Kneib, T., and Lang, S. (2005). BayesX: Analyzing Bayesian structured additive regression models. Journal of Statistical Software, 14, 11.
Eilers, P. H. C., and Marx, B. D. (1996). Flexible smoothing using B-splines and penalties. Statistical Science, 11, 89-121.
Entwisle, B., Casterline, J. B., and Sayed, H. A. A. (1989). Villages as contexts for contraceptive behaviour in rural Egypt. American Sociological Review, 54, 1019-1034.
Fahrmeir, L., Kneib, T., and Lang, S. (2004). Penalized additive regression for space-time data: A Bayesian perspective. Statistica Sinica, 14, 715-745.
Feng, W., and Quanhe, Y. (1996). Age at marriage and the first birth interval: the emerging change in sexual behaviour among young couples in china. Population and Development Review, 22, 299-320.
Gould, J. B., Herrchen, B., and Pham, T. (1998). Small-area analysis: targeting high-risk areas for adolescent pregnancy prevention programs. Family Planning Perspective, 30, 173–176.
Henry, L. (1973). Human Fertility: The Basic Components. Chicago: The University of Chicago.
Knorr-Held, L., Raber, G., and Becker, N. (2002). Disease mapping of stage-specific cancer incidence data. Biometrics, 25, 492-501.
Liu, I., and Agresti, A. (2005). The analysis of ordered categorical data: An overview and a survey of recent developments. Test, 14, 1-73.
Lloyd, C. B. (2005). Growing up Global: The Changing Transitions to Adulthood in Developing Countries. New York: National Academy Press.
Läärä, E., and Matthews, J. N. (1985). The equivalence of two models for ordinal data. Biometrika, 72, 206-207.
National Statistical Office and ORC Macro 2001. (2000). Malawi demographic and health survey 2000 [Computer software manual]. Zomba, Malawi: NSO.
Omori, Y. (2003). Discrete duration model having autoregressive random effects with application to Japanese diffusion index. Journal of the Japanese Statistical Society, 33, 1-22.
Tutz, G. (1991). Sequential models in ordinal regression. Computational Statistics and Data Analysis, 11, 275-295.
Tutz, G. (2003). Generalized semiparametrically structured ordinal models. Biometrics, 59, 263-273.
Tutz, G. (2005). Modelling of repeated ordered measurements by isotonic sequential regression. Statistical Modelling, 5, 269-287.
Zhang, W., and Steele, F. (2004). A semiparametric multilevel survival model. Journal of the Royal Statistical Society, Series C, 53, 387–404.
Zhenzhen, Z. (2000). Social-demographic influence on first birth interval in China, 1980-1992. Journal of Biosocial Sciences, 32, 315-327.
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