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Fitting the Best Model for ACEs Using Interrupted Time Series Data

A. Srinivasulu1 , B. Sarojamma2

Section:Research Paper, Product Type: Journal Paper
Volume-6 , Issue-6 , Page no. 753-760, Jun-2018

CrossRef-DOI:   https://doi.org/10.26438/ijcse/v6i6.753760

Online published on Jun 30, 2018

Copyright © A. Srinivasulu, B. Sarojamma . This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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IEEE Style Citation: A. Srinivasulu, B. Sarojamma, “Fitting the Best Model for ACEs Using Interrupted Time Series Data,” International Journal of Computer Sciences and Engineering, Vol.6, Issue.6, pp.753-760, 2018.

MLA Style Citation: A. Srinivasulu, B. Sarojamma "Fitting the Best Model for ACEs Using Interrupted Time Series Data." International Journal of Computer Sciences and Engineering 6.6 (2018): 753-760.

APA Style Citation: A. Srinivasulu, B. Sarojamma, (2018). Fitting the Best Model for ACEs Using Interrupted Time Series Data. International Journal of Computer Sciences and Engineering, 6(6), 753-760.

BibTex Style Citation:
@article{Srinivasulu_2018,
author = {A. Srinivasulu, B. Sarojamma},
title = {Fitting the Best Model for ACEs Using Interrupted Time Series Data},
journal = {International Journal of Computer Sciences and Engineering},
issue_date = {6 2018},
volume = {6},
Issue = {6},
month = {6},
year = {2018},
issn = {2347-2693},
pages = {753-760},
url = {https://www.ijcseonline.org/full_paper_view.php?paper_id=2250},
doi = {https://doi.org/10.26438/ijcse/v6i6.753760}
publisher = {IJCSE, Indore, INDIA},
}

RIS Style Citation:
TY - JOUR
DO = {https://doi.org/10.26438/ijcse/v6i6.753760}
UR - https://www.ijcseonline.org/full_paper_view.php?paper_id=2250
TI - Fitting the Best Model for ACEs Using Interrupted Time Series Data
T2 - International Journal of Computer Sciences and Engineering
AU - A. Srinivasulu, B. Sarojamma
PY - 2018
DA - 2018/06/30
PB - IJCSE, Indore, INDIA
SP - 753-760
IS - 6
VL - 6
SN - 2347-2693
ER -

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Abstract

The interrupted time series data plays a very important role in the evaluation of public health interventions and also to improve hospital antibiotic prescribing. We take the data from a study on the effects of the Italian smoking ban in public places on hospital admissions for Acute Coronary Events (ACEs). In January 2005, Italy introduced regulations to ban smoking in all indoor public places, which the aim of limiting adverse health affects of second hand smoke. The data used here are ACEs in the Sicily region between 2002 and 2006 among those aged 0-69 years. In this paper, we use three models for interrupted time series data. Root Mean Square Error (RMSE) measure is used for selecting the best model. Three models are empirically tested using interrupted time series smoke ban data in the Sicily region, Italy.

Key-Words / Index Term

ARIMA models, Before Intervention, After Intervention, Adaptive smoothing model, R2, RMSE.

References

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