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Journal articles on the topic 'Interrupted Time Series Analysis'

Author: Grafiati

Published: 4 June 2021

Last updated: 20 February 2023

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1

Matowe, Lloyd K., Cathie A. Leister, Concetta Crivera, and Joan M. Korth-Bradley. "Interrupted Time Series Analysis in Clinical Research." Annals of Pharmacotherapy 37, no. 7-8 (July 2003): 1110–16. http://dx.doi.org/10.1345/aph.1a109.

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OBJECTIVE: To demonstrate the usefulness of interrupted time series analysis in clinical trial design. METHODS: A safety data set of electrocardiographic (ECG) information was simulated from actual data that had been collected in a Phase I study. Simulated data on 18 healthy volunteers based on a study performed in a contract research facility were collected based on single doses of an experimental medication that may affect ECG parameters. Serial ECGs were collected before and during treatment with the experimental medication. Data from 7 real subjects receiving placebo were used to simulate the pretreatment phase of time series; data from 18 real subjects receiving active treatment were used to simulate the treatment phase of the time series. Visual inspection of data was performed, followed by tests for trend, seasonality, and autocorrelation by use of SAS. RESULTS: There was no evidence of trend, seasonality, or autocorrelation. In 11 of 18 simulated individuals, statistically significant changes in QTc intervals were observed following treatment with the experimental medication. A significant time of day and treatment interaction was observed in 4 simulated patients. CONCLUSIONS: Interrupted time series analysis techniques offer an additional tool for the study of clinical situations in which patients must act as their own controls and where serial data can be collected at evenly distributed intervals.

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McDonald, Terrence, Brendan Lethebe, Alistair McGuire, and Lee Green. "Time modifier billing code - an interrupted time series analysis." Canadian Journal of Emergency Nursing 44, no. 2 (July 20, 2021): 17. http://dx.doi.org/10.29173/cjen137.

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Time modifier billing code: Interrupted time series analysis. Terrence McDonald, Brendan Cord Lethebe, Alistair McGuire, Lee Green Background: Alberta has the highest percentage of fee-for-service Family Physicians in Canada at over 80%. In 2019 as part of a cost containment strategy, the Alberta government proposed a policy change to eliminate the most used fee code that compensates family physicians for extended visit times (16-25 minutes). Optimal length for patient visit times varies throughout the world and countries with health systems that place emphasis on relational continuity demonstrate a trend towards longer appointment times. In Canada, the relationship between visit length and outcomes is not known. Implementation: What would be the likely consequences of eliminating the extended visit code? We examined this question using two different observational methods, to improve confidence in our findings: a retrospective longitudinal cohort (time series) around the time the code was introduced in 2009, and a cross-sectional cohort at current time. We explored the usage patterns of that fee code, its association with the outcomes of emergency department visits and hospitalizations, along with physician billings. Results: We found rates of emergency department visits decreased after the time-modifier code was implemented starting in 2010. This effect was maintained in the years that followed. A similar but less pronounced effect was observed in the hospitalization rates. The cross-sectional analysis had to include an interaction term because family physicians selectively extend visits for patients at risk, but when that is accounted for, the same effect is observed as in longitudinal results. The code was not used ubiquitously among primary care providers, especially in rural areas. Female physicians used it more often. Users use it for an average of 40% of 03.03A office visits. Non-users of the code earned more income than their user-colleagues. Conclusion: We believe our findings will fill an important gap in informing the importance of an extended time service billing code in a fee-for-service system in reducing ED visits and hospitalizations. Advice and Lessons Learned: The fee-for-service time-modifier code, introduced in 2009, resulted in reduced ED visits and hospitalizations. It is likely that discontinuing the code would result in increased ED and hospital utilization, costing much more than removing the code would save. Usage of the time-modifier code was not uniform among primary care. Users of the code had different practice patterns and provider demographics. Our next step is to model the uptake of the code by primary care providers and explore the health system utilization and down-stream costs between users and non-users of the code.

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Wong, Ricky H., Fabrice Smieliauskas, I.-Wen Pan, and Sandi K. Lam. "Interrupted time-series analysis: studying trends in neurosurgery." Neurosurgical Focus 39, no. 6 (December 2015): E6. http://dx.doi.org/10.3171/2015.9.focus15374.

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OBJECT Neurosurgery studies traditionally have evaluated the effects of interventions on health care outcomes by studying overall changes in measured outcomes over time. Yet, this type of linear analysis is limited due to lack of consideration of the trend’s effects both pre- and postintervention and the potential for confounding influences. The aim of this study was to illustrate interrupted time-series analysis (ITSA) as applied to an example in the neurosurgical literature and highlight ITSA’s potential for future applications. METHODS The methods used in previous neurosurgical studies were analyzed and then compared with the methodology of ITSA. RESULTS The ITSA method was identified in the neurosurgical literature as an important technique for isolating the effect of an intervention (such as a policy change or a quality and safety initiative) on a health outcome independent of other factors driving trends in the outcome. The authors determined that ITSA allows for analysis of the intervention’s immediate impact on outcome level and on subsequent trends and enables a more careful measure of the causal effects of interventions on health care outcomes. CONCLUSIONS ITSA represents a significant improvement over traditional observational study designs in quantifying the impact of an intervention. ITSA is a useful statistical procedure to understand, consider, and implement as the field of neurosurgery evolves in sophistication in big-data analytics, economics, and health services research.

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Crosbie, John, and Christopher F. Sharpley. "DMITSA: A simplified interrupted time-series analysis program." Behavior Research Methods, Instruments, & Computers 21, no. 6 (November 1989): 639–42. http://dx.doi.org/10.3758/bf03210591.

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Crosbie, John. "Interrupted time-series analysis with brief single-subject data." Journal of Consulting and Clinical Psychology 61, no. 6 (1993): 966–74. http://dx.doi.org/10.1037/0022-006x.61.6.966.

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Ramsey, Patricia P., and Philip H. Ramsey. "Robust testing of level changes in interrupted time-series analysis." Journal of Statistical Computation and Simulation 76, no. 10 (October 2006): 913–23. http://dx.doi.org/10.1080/10629360500109069.

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7

Linden, Ariel. "Challenges to validity in single‐group interrupted time series analysis." Journal of Evaluation in Clinical Practice 23, no. 2 (September 14, 2016): 413–18. http://dx.doi.org/10.1111/jep.12638.

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Shenoy, Amrita G., Charles E. Begley, Lee Revere, Stephen H. Linder, and Stephen P. Daiger. "Innovating patient care delivery: DSRIP's interrupted time series analysis paradigm." Healthcare 7, no. 1 (March 2019): 44–50. http://dx.doi.org/10.1016/j.hjdsi.2017.11.004.

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9

Huitema, Bradley E. "Analysis of Interrupted Time-Series Experiments Using ITSE: A Critique." Understanding Statistics 3, no. 1 (February 2004): 27–46. http://dx.doi.org/10.1207/s15328031us0301_2.

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Sharpley, Christopher F. "Time-Series Analysis of Behavioural Data: An Update." Behaviour Change 4, no. 4 (December 1987): 40–45. http://dx.doi.org/10.1017/s0813483900008329.

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Some recent developments in the use of interrupted time-series analysis (ITSA) are described with particular reference to the detection of effects with short data series such as those often encountered in applied behaviour analysis. The necessity to perform the sometimes troublesome model-identification procedure is questioned, and the likely incidence of Type 1 and 2 errors is discussed. Conclusions are drawn to suggest that ITSA may be safely applied to data that are typical of those collected in applied behaviour analysis.

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Lee Rodgers, Joseph, William Howard Beasley, and Matthew Schuelke. "Graphical Data Analysis on the Circle: Wrap-Around Time Series Plots for (Interrupted) Time Series Designs." Multivariate Behavioral Research 49, no. 6 (November 2, 2014): 571–80. http://dx.doi.org/10.1080/00273171.2014.946589.

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Chen, Jing Bo, Jun Bao Zheng, Lei Yang, and Ya Ming Wang. "Change-Points Detections for Interrupted Time Series Analysis: A Literature Review." Applied Mechanics and Materials 462-463 (November 2013): 187–92. http://dx.doi.org/10.4028/www.scientific.net/amm.462-463.187.

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General review of Change-Points detection methods applied in Interrupted Time Series Analysis for recent years. Articles from domains like meteorology, hydrology, stock analysis, sequences mining et al. are compared together. The literatures range from the 1980s to 2013. The methods are generally classified in Parametric, Semi-Parametric, and Nonparametric. Some non-statistical methods are also mentioned in this review. Characters of each method are briefly summarized. As all methods mentioned in this review share a common purpose that to detect change-points, most of them can be used in other domains after some proper adjustment.

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Mpofu, Raphael Tabani. "Dollarization and economic development in Zimbabwe: An interrupted time-series analysis." Risk Governance and Control: Financial Markets and Institutions 5, no. 4 (2015): 38–48. http://dx.doi.org/10.22495/rgcv5i4art4.

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This paper examines the impact of dollarization on the performance of the Zimbabwean economy from 2003 to 2014 using an interrupted time-series analysis. In Zimbabwe’s case, dollarization was the official replacement of the Zimbabwean dollar with the U.S. dollar. Rapid dollarization in the economy was accelerated by the exogenous shock caused by the injection of cash dollars into the Zimbabwean economy, mostly from international transfers. Since the official adoption of dollarization, Zimbabwe is largely a cash-based economy, with a huge amount of U.S. dollars that are in circulation outside the banking system. A hands-off approach to currency management has served Zimbabwe well since 2009, but a number of risks are beginning to emerge as the economy has slowly regenerated itself and the need for large capital injections has increased. Macroeconomic data obtained from the World Bank and from the Reserve Bank of Zimbabwe’s Monthly Economic Review is analysed. According to the tests conducted, it was found that dollarization did introduce some macroeconomic stability in Zimbabwe although a few key macroeconomic variables showed a sustained improvement. Statistical analysis shows that increased dollarization had positively affected reversed the spiralling effects of hyperinflation that were prevalent prior to 2009, although inflationary pressures still continued, albeit at a slower pace. This research has implications not just for Zimbabwean policy makers as they grapple with decisions pertaining to re-adoption of a local currency and/or the continuation of the use of the US dollar and/or the adoption of a regional currency, for example, the South African rand. The African Union and specifically, the Southern Africa Development Community should look at these policy issues very closely in order to provide policy direction to its member states.

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Ewusie, Joycelyne E., Lehana Thabane, Joseph Beyene, Sharon E. Straus, and Jemila S. Hamid. "MultiCenter Interrupted Time Series Analysis: Incorporating Within and Between-Center Heterogeneity." Clinical Epidemiology Volume 12 (June 2020): 625–36. http://dx.doi.org/10.2147/clep.s231843.

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Geue, Claudia, James D. Lewsey, Daniel F. MacKay, Grace Antony, Colin M. Fischbacher, Jill Muirie, and Gerard McCartney. "Scottish Keep Well health check programme: an interrupted time series analysis." Journal of Epidemiology and Community Health 70, no. 9 (April 12, 2016): 924–29. http://dx.doi.org/10.1136/jech-2015-206926.

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Morgan, Oliver W., Clare Griffiths, and Azeem Majeed. "Interrupted Time-Series Analysis of Regulations to Reduce Paracetamol (Acetaminophen) Poisoning." PLoS Medicine 4, no. 4 (April 3, 2007): e105. http://dx.doi.org/10.1371/journal.pmed.0040105.

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Linden, Ariel. "Conducting Interrupted Time-series Analysis for Single- and Multiple-group Comparisons." Stata Journal: Promoting communications on statistics and Stata 15, no. 2 (June 2015): 480–500. http://dx.doi.org/10.1177/1536867x1501500208.

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Harrop, John W., and Wayne F. Velicer. "Computer Programs for Interrupted Time Series Analysis: I. A Qualitative Evaluation." Multivariate Behavioral Research 25, no. 2 (April 1990): 219–31. http://dx.doi.org/10.1207/s15327906mbr2502_12.

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Harrop, John W., and Wayne F. Velicer. "Computer Programs for Interrupted Time Series Analysis: II A Quantitative Evaluation." Multivariate Behavioral Research 25, no. 2 (April 1990): 233–48. http://dx.doi.org/10.1207/s15327906mbr2502_13.

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PEREZ, A. "An interrupted time series analysis of parenteral antibiotic use in Colombia." Journal of Clinical Epidemiology 56, no. 10 (October 2003): 1013–20. http://dx.doi.org/10.1016/s0895-4356(03)00163-x.

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21

Cooney, John B., John Clarke, and Grant L. Morris. "Analysis of the physiological stress profile: The interrupted time-series design." Biofeedback and Self-Regulation 11, no. 3 (September 1986): 231–45. http://dx.doi.org/10.1007/bf01003482.

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Linden, Ariel. "A Comprehensive set of Postestimation Measures to Enrich Interrupted Time-series Analysis." Stata Journal: Promoting communications on statistics and Stata 17, no. 1 (March 2017): 73–88. http://dx.doi.org/10.1177/1536867x1701700105.

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While the primary goal of interrupted time-series analysis (ITSA) is to evaluate whether there is a change in the level or trend of an outcome following an interruption (for example, policy change, intervention initiation), a series of additional measures may be relevant to the analysis. In this article, I seek to fill a gap in the ITSA literature by describing a comprehensive set of measures that can be computed following ITSA models, including those that fulfill the primary goal and those that provide supplementary information about trends. These measures can be calculated using the itsa command; this article therefore serves as a complement to “Conducting interrupted time-series analysis for single and multiple group comparisons” (Linden, 2015, Stata Journal 15: 480–500), which introduced the itsa command. Specific ITSA postestimation measures described in this article include individual trend lines, comparisons between multiple interventions, and comparisons with a counterfactual.

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23

Abdelgadir, Jihad, Cyrus Elahi, Jacquelyn Corley, Kevin C. Wall, Josephine N. Najjuma, Alex Muhindo, Joao Ricardo Nickenig Vissoci, Michael M. Haglund, and David Kitya. "Trends in neurosurgical care in Western Uganda: an interrupted time series analysis." Neurosurgical Focus 45, no. 4 (October 2018): E15. http://dx.doi.org/10.3171/2018.7.focus18270.

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OBJECTIVEIn addition to the rising burden of surgical disease globally, infrastructure and human resources for health remain a great challenge for low- and middle-income countries, especially in Uganda. In this study, the authors aim to explore the trends of neurosurgical care at a regional referral hospital in Uganda and assess the long-term impact of the institutional collaboration between Mulago National Referral Hospital and Duke University.METHODSAn interrupted time series is a quasi-experimental design used to evaluate the effects of an intervention on longitudinal data. The authors applied this design to evaluate the trends in monthly mortality rates for neurosurgery patients at Mbarara Regional Referral Hospital (MRRH) from March 2013 to October 2015. They used segmented regression and autoregressive integrated moving average models for the analysis.RESULTSOver the study timeframe, MRRH experienced significant increases in referrals received (from 117 in 2013 to 211 in 2015), neurosurgery patients treated (from 337 in 2013 to 625 in 2015), and operations performed (from 61 in 2013 to 173 in 2015). Despite increasing patient volumes, the hospital achieved a significant reduction in hospital mortality during 2015 compared to prior years (p value = 0.0039).CONCLUSIONSThis interrupted time series analysis study showed improving trends of neurosurgical care in Western Uganda. There is a steady increase in volume accompanied by a sharp decrease in mortality through the years. Multiple factors are implicated in the significant increase in volume and decrease in mortality, including the addition of a part-time neurosurgeon, improvement in infrastructure, and increased experience. Further in-depth prospective studies exploring seasonality and long-term outcomes are warranted.

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Orangi, Stacey, Angela Kairu, Lucas Malla, Joanne Ondera, Boniface Mbuthia, Nirmala Ravishankar, and Edwine Barasa. "Impact of free maternity policies in Kenya: an interrupted time-series analysis." BMJ Global Health 6, no. 6 (June 2021): e003649. http://dx.doi.org/10.1136/bmjgh-2020-003649.

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BackgroundUser fees have been reported to limit access to services and increase inequities. As a result, Kenya introduced a free maternity policy in all public facilities in 2013. Subsequently in 2017, the policy was revised to the Linda Mama programme to expand access to private sector, expand the benefit package and change its management.MethodsAn interrupted time-series analysis on facility deliveries, antenatal care (ANC) and postnatal care (PNC) visits data between 2012 and 2019 was used to determine the effect of the two free maternity policies. These data were from 5419 public and 305 private and faith-based facilities across all counties, with data sourced from the health information system. A segmented negative binomial regression with seasonality accounted for, was used to determine the level (immediate) effect and trend (month-on-month) effect of the policies.ResultsThe 2013 free-maternity policy led to a 19.6% and 28.9% level increase in normal deliveries and caesarean sections, respectively, in public facilities. There was also a 1.4% trend decrease in caesarean sections in public facilities. A level decrease followed by a trend increase in PNC visits was reported in public facilities. For private and faith-based facilities, there was a level decrease in caesarean sections and ANC visits followed by a trend increase in caeserean sections following the 2013 policy.Furthermore, the 2017 Linda Mama programme showed a level decrease then a trend increase in PNC visits and a 1.1% trend decrease in caesarean sections in public facilities. In private and faith-based facilities, there was a reported level decrease in normal deliveries and caesarean sections and a trend increase in caesarean sections.ConclusionThe free maternity policies show mixed effects in increasing access to maternal health services. Emphasis on other accessibility barriers and service delivery challenges alongside user fee removal policies should be addressed to realise maximum benefits in maternal health utilisation.

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Moineddin, Rahim, Christopher Meaney, and Sumeet Kalia. "Finite Sample Properties of Quantile Interrupted Time Series Analysis: A Simulation Study." Journal of the Iranian Statistical Society 20, no. 1 (June 1, 2021): 247–67. http://dx.doi.org/10.52547/jirss.20.1.247.

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Wagner, A. K., S. B. Soumerai, F. Zhang, and D. Ross-Degnan. "Segmented regression analysis of interrupted time series studies in medication use research." Journal of Clinical Pharmacy and Therapeutics 27, no. 4 (August 2002): 299–309. http://dx.doi.org/10.1046/j.1365-2710.2002.00430.x.

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Linden, Ariel. "A matching framework to improve causal inference in interrupted time-series analysis." Journal of Evaluation in Clinical Practice 24, no. 2 (December 20, 2017): 408–15. http://dx.doi.org/10.1111/jep.12874.

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Linden, Ariel. "Using permutation tests to enhance causal inference in interrupted time series analysis." Journal of Evaluation in Clinical Practice 24, no. 3 (February 20, 2018): 496–501. http://dx.doi.org/10.1111/jep.12899.

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Nestler, Matthew, John D. Markley, Andrew Noda, Emily Godbout, Jihye Kim, Kimberly B. Lee, Christopher Doern, et al. "74. Interrupted Time Series Analysis of the Impact of Fluoroquinolone Cascade Reporting." Open Forum Infectious Diseases 7, Supplement_1 (October 1, 2020): S55. http://dx.doi.org/10.1093/ofid/ofaa439.119.

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Abstract Background Cascade reporting is a form of selective reporting where antibiotic susceptibility results are revealed in a sequential order to optimize antibiotic use. On May 1, 2019, Virginia Commonwealth University Health implemented cascade reporting for ciprofloxacin and levofloxacin for E. coli from urine cultures. We hypothesize that suppressing fluoroquinolone (FQ) results for urine isolate E. coli susceptibility panels using cascade reporting led to a decrease in the overall rate of inpatient FQ use. Methods We compared inpatient FQ use (in days of therapy (DOT)/1000 patient days (PD)) for the one-year pre-cascade period (May 2018-April 2019) to the one-year post cascade period (May 2019-April 2020). Inpatient FQ use for May 2018-April 2020 was modeled as an interrupted time series (ITS) using ordinary least squares regression. The regression model followed the form of Y = B0 +B1T + B2 X + B3 XT with Y = (DOT/1,000 PD), T = time in months, X = cascade reporting represented with a binary digit, and XT= time since cascade reporting was implemented. Results were examined for autocorrelation and lag effects. Analysis conducted using Microsoft Excel and Python Statsmodel library v0.11.1. Results A segmented regression model was successfully fitted with R^2 = 0.73 (Figure 1). The pre-intervention slope (T), intervention change (X), and post-intervention slope (XT) were -3.9, -2.3, and 3.8 DOT respectively. A significant positive change in pre versus post intervention slope was detected (p = 0.01). Conclusion Results showed no significant change in FQ DOT/1000 PD when cascade reporting was implemented in May 2019. This may be due to empiric prescribing of FQs in the inpatient setting, due to the fact the rate of FQ use was already decreasing prior to cascade reporting adoption, or due to other factors. We detected a significant positive change in the slope of FQ from -4 to 4 DOT/1000 PD each month post-cascade reporting. Our hospital has had a decrease in FQ use over the past 8 years so this may be due to a ‘floor’ effect where the true minimum of necessary FQ use was reached; further investigation is warranted. We believe our data will be of interest to other Antimicrobial Stewardship Programs considering cascade reporting. Disclosures All Authors: No reported disclosures

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Cross, James P., and Jørgen Bølstad. "Openness and censorship in the European Union: An interrupted time series analysis." European Union Politics 16, no. 2 (December 12, 2014): 216–40. http://dx.doi.org/10.1177/1465116514560066.

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Harrop, John W., and Wayne F. Velicer. "A Comparison of Alternative Approaches to the Analysis of Interrupted Time-Series." Multivariate Behavioral Research 20, no. 1 (January 1985): 27–44. http://dx.doi.org/10.1207/s15327906mbr2001_2.

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Leiter, Valerie, Shelley K. White, and Abigail Walters. "Adverse Event Reports Associated with Vaginal Mesh: An Interrupted Time Series Analysis." Women's Health Issues 27, no. 3 (May 2017): 279–85. http://dx.doi.org/10.1016/j.whi.2017.01.005.

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Kemper, A. R., A. Helfrich, J. Talbot, N. Patel, and J. E. Crews. "Improving the Rate of Preschool Vision Screening: An Interrupted Time-Series Analysis." PEDIATRICS 128, no. 5 (October 10, 2011): e1279-e1284. http://dx.doi.org/10.1542/peds.2010-3679.

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Schaffer, Andrea L., Nicholas A. Buckley, Rose Cairns, and Sallie-Anne Pearson. "Interrupted Time Series Analysis of the Effect of Rescheduling Alprazolam in Australia." JAMA Internal Medicine 176, no. 8 (August 1, 2016): 1223. http://dx.doi.org/10.1001/jamainternmed.2016.2992.

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Penfold, Robert B., and Fang Zhang. "Use of Interrupted Time Series Analysis in Evaluating Health Care Quality Improvements." Academic Pediatrics 13, no. 6 (November 2013): S38—S44. http://dx.doi.org/10.1016/j.acap.2013.08.002.

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Sharpley, Christopher. "Fallability in the Visual Assessment of Behavioural Interventions: Time-Series Statistics to Analyse Time-Series Data." Behaviour Change 3, no. 1 (March 1986): 26–33. http://dx.doi.org/10.1017/s0813483900009074.

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The use of visual analysis alone to determine the presence of significant and generalizable effects in typical behavioural interventions is subject to a series of possible errors which result in high levels of unreliability when data are analysed in this way. The presence of autocorrelation in most behavioural data poses a serious threat to visual and traditional analysis of such data, a threat which can be avoided by use of the more appropriate interrupted time-series (TMS) statistics. Although previously suggested as reasons for not using TMS procedures, the issues of model-identification and number of data points required for TMS are discussed and shown to be invalid arguments against the use of TMS. A case is made for visual analysis of behavioural data as an appropriate procedure only under certain constrained clinical conditions.

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Druckman, Daniel. "Time-Series Designs and Analyses." International Negotiation 9, no. 3 (2004): 397–414. http://dx.doi.org/10.1163/1571806053498788.

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AbstractThis article describes the way time-series designs are used in research on international negotiation and related processes. Both quantitative and qualitative applications are discussed. One use of the techniques is to predict known outcomes of historical cases of negotiation. Both inductive and deductive approaches have been used in studies that evaluate alternative models of the way that negotiators respond to each other through the course of the talks. Another use of the techniques is to evaluate the impacts of such interventions as mediations or combat (referred to as interruptions) on the dynamics of conflict between nations. A third approach involves probabilistic forecasting with Bayesian analysis. This consists of revising initial probabilities of events (coups, peace agreements) based on current information about indicators that signal the occurrence of the event. Qualitative techniques have also been used to capture changes in conflict processes over time. These include charting changes in typological categories or in the use of influence strategies used by national actors in enduring rivalries. They also include tracing of paths to agreement or stalemate in negotiation, documenting progress in small-group dialogues, and developing chains of communication leading to peace agreements. By combining several of these techniques an analyst can draw conclusions about the likelihood that an event will occur (Bayesian analysis), its impact on a process (interrupted time series), and the way it emerged from prior events (process tracing).

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SAXÉN, HENRIK. "NONLINEAR TIME SERIES ANALYSIS BY NEURAL NETWORKS: A CASE STUDY." International Journal of Neural Systems 07, no. 02 (May 1996): 195–201. http://dx.doi.org/10.1142/s0129065796000166.

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This paper presents a neural network approach to time-series analysis of a univariate nonlinear system. Feedforward networks are studied, and an appropriate network size is determined by different criteria computed on the basis of the performance of the models on the training and test sets. The analysis and conclusions drawn are supported by studies of the phase portraits of the models. By a proper choice of network size, the problems of over-parameterization are demonstrated to be avoided. The overfitting observed for larger networks is analyzed and the underlying reasons for their worse generalization capabilities are explained. Finally, some observations are made on the approximation provided by an oversized network with weights determined by an incomplete (interrupted) training and that of the optimal-sized network.

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Xiong, Yao, Judy Xu, and Yuexia Gao. "Does price deregulation increase drug price in China? An interrupted time series analysis." International Journal of Health Planning and Management 36, no. 5 (May 24, 2021): 1653–65. http://dx.doi.org/10.1002/hpm.3244.

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Holmes, Malcolm D., Howard C. Daudistel, and William A. Taggart. "Plea Bargaining Policy and State District Court Caseloads: An Interrupted Time Series Analysis." Law & Society Review 26, no. 1 (1992): 139. http://dx.doi.org/10.2307/3053839.

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Linden, Ariel. "Erratum: A comprehensive set of postestimation measures to enrich interrupted time-series analysis." Stata Journal: Promoting communications on statistics and Stata 22, no. 1 (March 2022): 231–33. http://dx.doi.org/10.1177/1536867x221083929.

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Yang, Bo-Ram, Kyu-Nam Heo, Yun Mi Yu, Ga-Bin Yeom, Hye Duck Choi, Ju-Yeun Lee, and Young-Mi Ah. "Interrupted Time Series Analysis of Changes in Zolpidem Use Due to Media Broadcasts." International Journal of Environmental Research and Public Health 18, no. 10 (May 12, 2021): 5114. http://dx.doi.org/10.3390/ijerph18105114.

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Media has become a major source of information on health and plays a role in the decision-making process on health topics. We aimed to evaluate the association between zolpidem use and media broadcasts that reported the suicide risk. We obtained the data of adult outpatients who have been prescribed zolpidem or other hypnotics from the National Patient Sample database (2015–2017). We evaluated the change in zolpidem or other hypnotic prescription trends based on the prescription rate and average daily prescribed dose before and after July 2016, using interrupted time series analysis. A total of 129,787 adult patients had at least one zolpidem prescription in 3 years. The prescription rate of zolpidem after the broadcast decreased significantly by 0.178% (95% confidence interval (CI): −0.214, −0.142), whereas that of other hypnotic users did not differ from that before the broadcast (−0.020%, 95% CI: −0.088, 0.047). However, the trends in the prescription rate before and after the broadcast did not differ for zolpidem and other hypnotics. Broadcasting medication safety through major public media could have an effect on medication use. After broadcasting about the suicide risk of zolpidem, its overall prescription rate decreased immediately, but the trend was not changed.

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Bazo-Alvarez, Juan Carlos, Tim P. Morris, Tra My Pham, James R. Carpenter, and Irene Petersen. "Handling Missing Values in Interrupted Time Series Analysis of Longitudinal Individual-Level Data." Clinical Epidemiology Volume 12 (October 2020): 1045–57. http://dx.doi.org/10.2147/clep.s266428.

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Ramsey, Patricia, and Philip Ramsey. "Comparing least-squares lines for testing level changes in interrupted time-series analysis." Journal of Statistical Computation and Simulation 73, no. 1 (January 2003): 31–44. http://dx.doi.org/10.1080/00949650215724.

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Hanna, Catherine, Jose Antonio Robles-Zurita, Philip McLoone, Caroline Kelly, Kathleen Boyd, and Robert J. Jones. "Real-life implementation of the SCOT trial findings: An interrupted time series analysis." Journal of Clinical Oncology 38, no. 15_suppl (May 20, 2020): e19341-e19341. http://dx.doi.org/10.1200/jco.2020.38.15_suppl.e19341.

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e19341 Background: The Short Course Oncology Treatment (SCOT) trial demonstrated that three months of adjuvant, doublet chemotherapy for patients with colorectal cancer was non-inferior and significantly less toxic than six months. To understand if and how these results were implemented, this study analysed prescribing practice before and after dissemination of the SCOT results at a population level. Methods: Individual electronic records for patients in a Scottish health board (population 1.1 million) were reviewed (January 2010-June 2019) to explore the proportion of patients receiving over three months of treatment pre and post-SCOT. Logistic and linear regression were used in an interrupted time series analysis to estimate prescribing practices, and to assess the counterfactual situation in which the trial had not occurred. Patients receiving single agent chemotherapy were the comparator group. Predictors of patients receiving a longer duration of treatment post-SCOT were also identified. Results: In total, 998 patients received adjuvant chemotherapy; 564 doublet and 434 single agent. For those prescribed doublet chemotherapy, there was a significant decrease in the proportion receiving more than 3 months of treatment after the SCOT trial results (20%) versus pre-SCOT (84%, p < 0.001). Disease risk was a key predictor for longer duration of treatment post-SCOT. Table outlines the predicted practice post-SCOT (June 2019) for the modelled and counterfactual scenarios. Conclusions: A clear change in treatment duration for patients receiving doublet chemotherapy was observed. Disease stage influencing post-SCOT prescribing aligns with recently updated clinical guidelines. This methodology can be applied to explore the implementation of future trials and to highlight any barriers to implementation that exist. [Table: see text]

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Tarlow, Kevin R., and Daniel F. Brossart. "A comprehensive method of single-case data analysis: Interrupted Time-Series Simulation (ITSSIM)." School Psychology Quarterly 33, no. 4 (December 2018): 590–603. http://dx.doi.org/10.1037/spq0000273.

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Fleming, J. N., D. J. Taber, D. Axelrod, and K. D. Chavin. "The effect of Share 35 on biliary complications: An interrupted time series analysis." American Journal of Transplantation 19, no. 1 (June 11, 2018): 221–26. http://dx.doi.org/10.1111/ajt.14937.

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Ramirez, Juan R., and William D. Crano. "Deterrence and Incapacitation: An Interrupted Time-Series Analysis of California's Three-Strikes Law1." Journal of Applied Social Psychology 33, no. 1 (January 2003): 110–44. http://dx.doi.org/10.1111/j.1559-1816.2003.tb02076.x.

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Allam, B., G. Saadeh, and G. Kiwan. "PDG35 Generic Substitution in Lebanon: A Controlled Interrupted Time Series Analysis of Statins." Value in Health 23 (December 2020): S525—S526. http://dx.doi.org/10.1016/j.jval.2020.08.718.

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Pérez-Rubio, Alberto, Francisco Javier Luquero, Maria Rosario Bachiller Luque, Paz de la Torre Pardo, and José María Eiros Bouza. "Impact of the rotavirus vaccine in Valladolid, Spain: An interrupted time series analysis." Trials in Vaccinology 5 (2016): 84–87. http://dx.doi.org/10.1016/j.trivac.2016.04.005.

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