Group regularization for zero-inflated poisson regression models with an application to insurance ratemaking

2018 ◽  
Vol 46 (9) ◽  
pp. 1567-1581 ◽  
Author(s):  
Shrabanti Chowdhury ◽  
Saptarshi Chatterjee ◽  
Himel Mallick ◽  
Prithish Banerjee ◽  
Broti Garai
Author(s):  
Dafina Petrova ◽  
Marina Pollán ◽  
Miguel Rodriguez-Barranco ◽  
Dunia Garrido ◽  
Josep M. Borrás ◽  
...  

Abstract Background The patient interval—the time patients wait before consulting their physician after noticing cancer symptoms—contributes to diagnostic delays. We compared anticipated help-seeking times for cancer symptoms and perceived barriers to help-seeking before and after the coronavirus pandemic. Methods Two waves (pre-Coronavirus: February 2020, N = 3269; and post-Coronavirus: August 2020, N = 1500) of the Spanish Onco-barometer population survey were compared. The international ABC instrument was administered. Pre–post comparisons were performed using multiple logistic and Poisson regression models. Results There was a consistent and significant increase in anticipated times to help-seeking for 12 of 13 cancer symptoms, with the largest increases for breast changes (OR = 1.54, 95% CI 1.22–1–96) and unexplained bleeding (OR = 1.50, 1.26–1.79). Respondents were more likely to report barriers to help-seeking in the post wave, most notably worry about what the doctor may find (OR = 1.58, 1.35–1.84) and worry about wasting the doctor’s time (OR = 1.48, 1.25–1.74). Women and older individuals were the most affected. Conclusions Participants reported longer waiting times to help-seeking for cancer symptoms after the pandemic. There is an urgent need for public interventions encouraging people to consult their physicians with symptoms suggestive of cancer and counteracting the main barriers perceived during the pandemic situation.


2021 ◽  
Vol 215 ◽  
pp. 288-318
Author(s):  
Youssef Kassem ◽  
Hüseyin Gökçekuş

2011 ◽  
Vol 34 (4) ◽  
pp. 575-582 ◽  
Author(s):  
Fabyano Fonseca Silva ◽  
Karen P. Tunin ◽  
Guilherme J.M. Rosa ◽  
Marcos V.B. da Silva ◽  
Ana Luisa Souza Azevedo ◽  
...  

Author(s):  
Ajitabh Dash

The purpose of this study is to analyse how various dimensions brand post characteristics, such as vividness, novelty and content type, influence the online engagement on Facebook brand pages managed by small and medium enterprises (SMEs) in India. A sample of 162 brand posts published by 10 brand pages managed by SMEs in India for a selected time period between 1 April and 1 June 2019. Poisson regression models were deployed to analyse the collected data and assess the effect of these brand post characteristics on online engagement. The findings of this study not only contribute to the existing literature but also will help the SMEs to craft their content strategy for social media marketing in Indian context.


2009 ◽  
Vol 138 (6) ◽  
pp. 836-842 ◽  
Author(s):  
A. T. NEWALL ◽  
C. VIBOUD ◽  
J. G. WOOD

SUMMARYThis study aimed to compare systematically approaches to estimating influenza-attributable mortality in older Australians. Using monthly age-specific death data together with viral surveillance counts for influenza and respiratory syncytial virus, we explored two of the most frequently used methods of estimating excess influenza-attributable disease: Poisson and Serfling regression models. These approaches produced consistent age and temporal patterns in estimates of influenza-attributable mortality in older Australians but some variation in the magnitude of the disease burden. Of Australians aged >50 years, average annual estimated influenza-attributable deaths (all cause) ranged from 2314 to 3457 for the Serfling and Poisson regression models, respectively. The excess influenza-attributable disease burden was substantial under all approaches.


1994 ◽  
Vol 73 (2) ◽  
pp. 573-579 ◽  
Author(s):  
P.P. Hujoel ◽  
P.J. Isokangas ◽  
J. Tiekso ◽  
S. Davis ◽  
R.J. Lamont ◽  
...  

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