Threshold detection by fitting segmented regression models in Microsoft Excel [PDF]
MethodsXWe present a generally applicable method for segmented regression analysis, which is suitable for describing data that follow two distinct functions that meet at an unknown transition or break point and is particularly useful for detecting thresholds ...
Amy J Hopper, Angus M Brown
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Optimized segmented regression models for the transition period of intervention effects [PDF]
Global Health Research and Policy, 2023 Background The interrupted time series (ITS) design is a widely used approach to examine the effects of interventions. However, the classic segmented regression (CSR) method, the most popular statistical technique for analyzing ITS data, may not be ...
Xiangliang Zhang +7 more
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Consistent model selection in segmented line regression [PDF]
Journal of Statistical Planning and Inference, 2016 The Schwarz criterion or Bayes Information Criterion (BIC) is often used to select a model dimension, and some variations of the BIC have been proposed in the context of change-point problems. In this paper, we consider a segmented line regression model with an unknown number of change-points and study asymptotic properties of Schwarz type criteria in ...
Kim, Jeankyung, Kim, Hyune-Ju
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Impact of a Multifaceted Pharmacist-Led Intervention on Antimicrobial Stewardship in a Gastroenterology Ward: A Segmented Regression Analysis [PDF]
Frontiers in Pharmacology, 2020 BackgroundIrrational use of antimicrobial agents for gastrointestinal diseases deserves attention, but corresponding antimicrobial stewardship programs (ASPs) are generally not a priority for managers.
Yaling Du +10 more
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Epidemiological monitoring of leprosy indicators in Sergipe (2001-2015): segmented regression analysis, [PDF]
Anais Brasileiros de Dermatologia, 2020 This study analyzed the trend of leprosy indicators in Sergipe, between 2001 and 2015. It was a time series study that analyzed the trend for general detection coefficient, children under 15 years of age, and new cases with grade 2 disability.
Carlos Dornels Freire de Souza +3 more
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Interpretation of coefficients in segmented regression for interrupted time series analyses [PDF]
BMC Medical Research MethodologyBackground Segmented regression, a common model for interrupted time series (ITS) analysis, primarily utilizes two equation parametrizations. Interpretations of coefficients vary between the two segmented regression parametrizations, leading to ...
Yongzhe Wang +5 more
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International Journal of Preventive Medicine, 2016 Background: Describing trend in tuberculosis (TB) over time can play an important role to assess the disease control strategies and predict the future morbidity and mortality.
Salman Khazaei +5 more
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piecewise-regression (aka segmented regression) in Python [PDF]
Journal of Open Source Software, 2021 Charlie Pilgrim
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Reflection on modern methods: a common error in the segmented regression parameterization of interrupted time-series analyses. [PDF]
Int J Epidemiol, 2021 Xiao H, Augusto O, Wagenaar BH.
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A Method of Accuracy Increment Using Segmented Regression
Algorithms, 2022 The main purpose of mathematical model building while employing statistical data analysis is to obtain high accuracy of approximation within the range of observed data and sufficient predictive properties.
Jamil Al-Azzeh +4 more
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