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Title | Biostat III – Survival analysis for epidemiologists in Stata (6-15 February |
Description | to allow for id="wrapper" --> Biostat III – Survival analysis for epidemiologists in Stata (6-15 February 2023) HOME SCHEDULE DOWNLOAD FACULTY Contact |
Keywords | N/A |
WebSite | biostat3.net |
Host IP | 66.96.149.19 |
Location | United States |
Site | Rank |
US$1,174,456
Last updated: 2023-05-16 07:57:05
biostat3.net has Semrush global rank of 9,012,091. biostat3.net has an estimated worth of US$ 1,174,456, based on its estimated Ads revenue. biostat3.net receives approximately 135,515 unique visitors each day. Its web server is located in United States, with IP address 66.96.149.19. According to SiteAdvisor, biostat3.net is safe to visit. |
Purchase/Sale Value | US$1,174,456 |
Daily Ads Revenue | US$1,085 |
Monthly Ads Revenue | US$32,524 |
Yearly Ads Revenue | US$390,281 |
Daily Unique Visitors | 9,035 |
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biostat3.net. | A | 3600 | IP: 66.96.149.19 |
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biostat3.net. | NS | 3600 | NS Record: ns2.netfirms.com. |
biostat3.net. | MX | 3600 | MX Record: 30 mx.biostat3.net. |
biostat3.net. | TXT | 3600 | TXT Record: v=spf1 ip4:66.96.128.0/18 ?all |
to allow for id="wrapper" --> Biostat III – Survival analysis for epidemiologists in Stata (6-15 February 2023) HOME SCHEDULE DOWNLOAD FACULTY Contact Welcome to the Biostatistics III in Stata course for spring 2023. This course introduces statistical methods for survival analysis with emphasis on the application of such methods to the analysis of epidemiological cohort studies. Topics covered include methods for estimating patient survival (life table and Kaplan-Meier methods), comparing survival between patient subgroups (log-rank test), and modelling survival (primarily Poisson regression, Cox proportional hazards model and flexible parametric models). The course addresses the concept of ’time’ as a potential confounder or effect modifier and approaches to defining ’time’ (e.g., time since entry, attained age, calendar time). The course will emphasise the basic concepts of statistical modelling in epidemiology, such as controlling for confounding and assessing effect |
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