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Subset of data from the POPS study, a national, prospective study on preterm children, including all liveborn infants <32 weeks gestational age and/or <1500 g from 1983 (n = 1338).

Format

pops is a data frame with 959 rows and 86 columns. pops.pred is the 86 by 86 binary predictor matrix used for specifying the multiple imputation model.

Source

Hille, E. T. M., Elbertse, L., Bennebroek Gravenhorst, J., Brand, R., Verloove-Vanhorick, S. P. (2005). Nonresponse bias in a follow-up study of 19-year-old adolescents born as preterm infants. Pediatrics, 116(5):662666.

Hille, E. T. M., Weisglas-Kuperus, N., Van Goudoever, J. B., Jacobusse, G. W., Ens-Dokkum, M. H., De Groot, L., Wit, J. M., Geven, W. B., Kok, J. H., De Kleine, M. J. K., Kollee, L. A. A., Mulder, A. L. M., Van Straaten, H. L. M., De Vries, L. S., Van Weissenbruch, M. M., Verloove-Vanhorick, S. P. (2007). Functional outcomes and participation in young adulthood for very preterm and very low birth weight infants: The Dutch project on preterm and small for gestational age infants at 19 years of age. Pediatrics, 120(3):587595.

Van Buuren, S. (2018). Flexible Imputation of Missing Data. Second Edition. Chapman & Hall/CRC. Boca Raton, FL.

Details

The data set concerns of subset of 959 children that survived up to the age of 19 years.

Hille et al (2005) divided the 959 survivors into three groups: Full responders (examined at an outpatient clinic and completed the questionnaires, n = 596), postal responders (only completed the mailed questionnaires, n = 109), non-responders (did not respond to any of the mailed requests or telephone calls, or could not be traced, n = 254).

Compared to the postal and non-responders, the full response group consists of more girls, contains more Dutch children, has higher educational and social economic levels and has fewer handicaps. The responders form a highly selective subgroup in the total cohort.

Multiple imputation of this data set has been described in Hille et al (2007) and Van Buuren (2012), chapter 8.

Note

This dataset is not part of mice.

Examples

pops <- data(pops)