ArticlePopulation health metrics2003
Autoregression as a means of assessing the strength of seasonality in a time series.
Article in Population health metrics, 2003. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 21 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
21 citing papers in PubMed.
- Addressing the Knowledge Deficit in Hospital Bed Planning and Defining an Optimum Region for the Number of Different Types of Hospital Beds in an Effective Health Care System.International journal of environmental research and public health · 2023Review
- Impact of Ontario's Harmonized Heat Warning and Information System on emergency department visits for heat-related illness in Ontario, Canada: a population-based time series analysis.Canadian journal of public health = Revue canadienne de sante publique · 2022Article
- Impact of provincial and national implementation strategies on P2Y12 inhibitor utilization for acute coronary syndrome in the elderly: an interrupted time series analysis from 2008 to 2018.Implementation science : IS · 2021Article
- Exploration of the STOP Act and Opioid Deaths in North Carolina, 2010-2018.American journal of public health · 2020Article
- Hip Fractures in Older Adults in Ontario, Canada-Monthly Variation, Insights, and Implications.Canadian geriatrics journal : CGJ · 2019Article
- Article
- Impact of the End Stage Renal Disease Prospective Payment System on the Use of Peritoneal Dialysis.Kidney international reports · 2017Article
- Bacterial meningitis in Malawian adults, adolescents, and children during the era of antiretroviral scale-up and Haemophilus influenzae type b vaccination, 2000-2012.Clinical infectious diseases : an official publication of the Infectious Diseases Society of America · 2014Article
- Invasive bacterial infections following influenza: a time-series analysis in Montréal, Canada, 1996-2008.Influenza and other respiratory viruses · 2012Article
- Comparing statistical models to predict dengue fever notifications.Computational and mathematical methods in medicine · 2012Article
- Excess risk of head and chest colds among teachers and other school workers.The Journal of school health · 2011Article
- Temporal and longitudinal analysis of Danish Swine Salmonellosis Control Programme data: implications for surveillance.Epidemiology and infection · 2008Article
- Seasonality of primary care utilization for respiratory diseases in Ontario: a time-series analysis.BMC health services research · 2008Article
- Fourteen-year study of hospital admissions for diverticular disease in Ontario.Canadian journal of gastroenterology = Journal canadien de gastroenterologie · 2007Article
- Seasonality of service provision in hip and knee surgery: a possible contributor to waiting times? A time series analysis.BMC health services research · 2006Article
- Time series analysis of age related cataract hospitalizations and phacoemulsification.BMC ophthalmology · 2006Article
- Using autoregressive integrated moving average (ARIMA) models to predict and monitor the number of beds occupied during a SARS outbreak in a tertiary hospital in Singapore.BMC health services research · 2005Article
- Simplicity within complexity: seasonality and predictability of hospital admissions in the province of Ontario 1988-2001, a population-based analysis.BMC health services research · 2005Article
- Effect of gender, age, and severity of asthma attack on patterns of emergency department visits due to asthma by month and day of the week.European journal of epidemiology · 2005Article
- Is there a clinically significant seasonal component to hospital admissions for atrial fibrillation?BMC health services research · 2004Article
Corrections and comments
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Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundThe study of the seasonal variation of disease is receiving increasing attention from health researchers. Available statistical tests for seasonality typically indicate the presence or absence of statistically significant seasonality but do not provide a meaningful measure of its strength.
methodsWe propose the coefficient of determination of the autoregressive regression model fitted to the data () as a measure for quantifying the strength of the seasonality. The performance of the proposed statistic is assessed through a simulation study and using two data sets known to demonstrate statistically significant seasonality: atrial fibrillation and asthma hospitalizations in Ontario, Canada.
resultsThe simulation results showed the power of the in adequately quantifying the strength of the seasonality of the simulated observations for all models. In the atrial fibrillation and asthma datasets, while the statistical tests such as Bartlett's Kolmogorov-Smirnov (BKS) and Fisher's Kappa support statistical evidence of seasonality for both, the quantifies the strength of that seasonality. Corroborating the visual evidence that asthma is more conspicuously seasonal than atrial fibrillation, the calculated for atrial fibrillation indicates a weak to moderate seasonality ( = 0.44, 0.28 and 0.45 for both genders, males and females respectively), whereas for asthma, it indicates a strong seasonality ( = 0.82, 0.78 and 0.82 for both genders, male and female respectively).
conclusionsFor the purposes of health services research, evidence of the statistical presence of seasonality is insufficient to determine the etiologic, clinical and policy relevance of findings. Measurement of the strength of the seasonal effect, as can be determined using the technique, is also important in order to provide a robust sense of seasonality.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.