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8. Power Computations for Intervention Analysis

Author

McLeod, A. Ian and Vingilis, Evelyn R.

Subjects
Mathematics - Statistics Theory, 62M10, 91B84
Abstract

In many intervention analysis applications time series data may be expensive or otherwise difficult to collect. In this case the power function is helpful since it can be used to determine the probability that a proposed intervention analysis application will detect a meaningful change. Assuming that an underlying ARIMA or fractional ARIMA model is known or can be estimated from the pre-intervention time series, the methodology for computing the required power function is developed for pulse, step and ramp interventions with ARIMA and fractional ARIMA errors. Convenient formulae for computing the power function for important special cases are given. Illustrative applications in traffic safety and environmental impact assessment are discussed., Comment: 28 pages, 3 figures, 8 tables

Published
2016
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10. Adult attention-deficit hyperactivity disorder symptoms and psychological distress, hazardous drinking, and problem gambling: A population-based study

Author

McDonald, André J., Cook, Steven, Turner, Nigel E., Ialomiteanu, Anca R., Mann, Robert E., Bondy, Susan J., Roerecke, Michael, McCready, John, Millstone, Dov, Hamilton, Hayley A., Elton-Marshall, Tara, Rehm, Jürgen, Kurdyak, Paul, Ilie, Gabriela, Vingilis, Evelyn R., Wickens, Christine M., van der Maas, Mark, and Cusimano, Michael D.

Published
2021
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35. Analysis of secondary data: Considerations revisited

Author

Pederson Linda L, Koval John J, and Vingilis Evelyn

Abstract

In a recent publication, we discussed the benefits and cautions of using secondary data analyses in research on lifestyle and health behavior [1]. We provided some guidelines about the use of secondary data in terms of the contributions that can be made and at the same time considerations necessary in using data that are collected by someone else. The use of secondary data to explore social and health issues results in being able to provide information about important issues in a timely fashion. Secondary data can answer two types of questions: descriptive and analytical [2]. Hence, the information can be used to describe events or trends or it can be used to examine relationships among variables cross-sectionally or longitudinally.

Published
2022

49. Predictors of Adolescent Health Care Utilization

Author

Vingilis, Evelyn, Wade, Terrance, and Seeley, Jane

Abstract

This study, using Andersen's health care utilization model, examined how predisposing characteristics, enabling resources, need, personal health practices, and psychological factors influence health care utilization using a nationally representative, longitudinal sample of Canadian adolescents. Second, this study examined whether this process varies across physicians, non-physicians, and dentists. The results indicate that need and psychological factors were strong determinants of utilization. Predisposing factors were associated with utilization, although there were few enabling resources. Differences were found for utilization of different services. Females, adolescents who were older, from single parent families, with lower self-rated health, lower health status, higher disability, higher distress and involved in health compromizing practices were more likely to visit physicians and non-physicians. Higher dentist utilization was related to higher income, single parent status, being younger, having lower health status, and higher disability. Predisposing and enabling factors were not mediators of utilization. The findings suggest that health care providers could be an important source of counselling on psychological, lifestyle issues, and physical concerns.

Published
2007
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