scholarly journals The Chi-Squared Goodness-of-Fit Test for Count-Data Models

Author(s):  
Miguel Manjón ◽  
Oscar Martínez
Biometrics ◽  
2009 ◽  
Vol 66 (2) ◽  
pp. 426-434 ◽  
Author(s):  
Jing Cao ◽  
Ann Moosman ◽  
Valen E. Johnson

1994 ◽  
Vol 4 (3) ◽  
pp. 205-221 ◽  
Author(s):  
Rainer Winkelmann ◽  
Klaus F. Zimmermann

2021 ◽  
Vol 39 (15_suppl) ◽  
pp. e14050-e14050
Author(s):  
Olusola Michael Adeleke ◽  
Rubyyat A Hakim ◽  
Laurence Dean ◽  
Huma Zahid ◽  
Rongyu Lin ◽  
...  

e14050 Background: Historically, metastatic spinal cord compression (MSCC) referrals trend towards a Friday peak in incidence (Koiter E, Radioth Onc 2013). However, data from a single, tertiary centre in the UK showed a reversal in the Friday peak (Adeleke S, Annals of Oncology 2020). This was attributed to early case referrals and quicker treatment decisions. In this new study, we explored whether a similar pattern was apparent in multiple district general hospital (DGH) settings and attempt to identify underlying causes. DGHs manage a larger proportion of cancer patients in the UK. Methods: 1,069 patients between 1 Jan 2015 and 31 Dec 2020 were identified across 4 hospitals in Kent, UK with a population of 1.6 million people. 220, 181, 182, 159, 134 and 193 MSCC patients were identified annually (2015-2020). Commonest cancers were prostate (24.1%), lung (19.3%) and breast (12.3%). Thoracic and lumbar regions constituted 80% of MSCC sites. Kruskal Wallis was used to compare differences in referrals across weekdays. Data was then dichotomised to Fridays only vs. other days of the week combined, as previously reported (De Bono B, Acta Neurochir 2019). Chi squared was used to compare frequency of referrals between the two groups. Chi squared goodness of fit test was conducted to detect if Friday reflected the day with highest referrals across the week. Results: Across the region, 2015 saw the highest number of Friday referrals relative to other days, p= 0.002. Friday referrals continued to drop, year on year, until 2018 with a corresponding increase in mid-week referrals. After 2018, there was a return in trend to a further Friday peak across the region, though p= 0.836. On an individual hospital basis, the persistent Friday peak in the region was driven by two hospitals. Having a 7-day acute oncology service (AOS), 7-day radiology reporting and single referral point of contact in the department, were factors identified that kept the referrals across the week uniform. On another note, a substantial shift towards a single 8Gy fraction vs. 20Gy in 5 fractions was observed across the region. This change coincided with SCORAD III data (Hoskin P, ASCO 2017) and demonstrates adherence to evidence-based practice in the region. Conclusions: This large multi-centre retrospective study shows a differential referral pattern in the region, with hospitals with 7-day AOS/Radiology reporting and single point of referral (e.g, similar to MSCC coordinator role) having a quicker treatment turnaround and uniform referrals across the week. The MSCC coordinator has been shown to streamline service, ensure timely decision-making and improved survival outcomes (Richards L, Spine J 2017). The role is recommended by NICE UK. DGHs should consider appointing an MSCC coordinator when designing/auditing their service. The shift towards single 8Gy fraction can provide a ‘one-stop’ service where patients are scanned, planned and treated on the same day.


2021 ◽  
Vol 3 (1) ◽  
pp. 1-13
Author(s):  
Muhammad Anus Hayat Khan ◽  
Ijaz Hussain

Each year more than three thousand people die and get serious injuries in traffic accidents. Count data model provide more precise tools for planners and decision makers to conduct proactive road safety planning.We analyzed the exploratory research of Road Traffic Accidents (RTAs) and furthermore explores the factors affecting the RTAs frequency in 36 districts of the Punjab over a time period of three years (July 1, 2013 June 30, 2016) with monthly data using panel count data models. Among the models considered, the random parameters Poisson panel count data model is found to fit the data best. The exploratory analysis shows that highly dense populated districts with large number of registered vehicles causes more accidents as compared to low density populated districts. It is found that, most of the variables used to control the variation in the frequency of RTAs counts play vital role with higher significance levels. The application of regression analysis and modeling of RTAs at district level in Punjab will help to identification of districts with high RTAs rates and this could help more efficient road safety management in the Punjab.


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