Self-Controlled Case Series Studies
Self-Controlled Case Series Studies: A Modelling Guide with R provides the first comprehensive account of the self-controlled case series (SCCS) method, a statistical technique for investigating associations between outcome events and time-varying exposures. The method only requires information from...
Sábháilte in:
| Príomhchruthaitheoirí: | , , |
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| Formáid: | Online |
| Teanga: | Béarla |
| Foilsithe / Cruthaithe: |
Taylor & Francis
2024
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| Ábhair: | |
| Rochtain ar líne: | OCN: 1035389982 |
| Clibeanna: |
Níl clibeanna ann, Bí ar an gcéad duine le clib a chur leis an taifead seo!
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| _version_ | 1869526746032766976 |
|---|---|
| author | Farrington, Paddy Whitaker, Heather Ghebremichael-Weldeselassie, Yonas |
| author_browse | Farrington, Paddy Ghebremichael-Weldeselassie, Yonas Whitaker, Heather |
| author_facet | Farrington, Paddy Whitaker, Heather Ghebremichael-Weldeselassie, Yonas |
| author_sort | Farrington, Paddy |
| collection | Directory of Open Access Books |
| description | Self-Controlled Case Series Studies: A Modelling Guide with R provides the first comprehensive account of the self-controlled case series (SCCS) method, a statistical technique for investigating associations between outcome events and time-varying exposures. The method only requires information from individuals who have experienced the event of interest, and automatically controls for multiplicative time-invariant confounders, even when these are unmeasured or unknown. It is increasingly being used in epidemiology, most frequently to study the safety of vaccines and pharmaceutical drugs.
Key features of the book include:
A thorough yet accessible description of the SCCS method, with mathematical details provided in separate starred sections.
Comprehensive discussion of assumptions and how they may be verified.
A detailed account of different SCCS models, extensions of the SCCS method, and the design of SCCS studies.
Extensive practical illustrations and worked examples from epidemiology.
Full computer code from the associated R package SCCS, which includes all the data sets used in the book.
The book is aimed at a broad range of readers, including epidemiologists and medical statisticians who wish to use the SCCS method, and also researchers with an interest in statistical methodology. The three authors have been closely involved with the inception, development, popularisation and programming of the SCCS method. |
| format | Online |
| id | doab-20.500.12854ir-138074 |
| institution | Directory of Open Access Books |
| language | eng |
| publishDate | 2024 |
| publishDateRange | 2024 |
| publishDateSort | 2024 |
| publisher | Taylor & Francis |
| publisherStr | Taylor & Francis |
| record_format | ojs |
| spelling | doab-20.500.12854ir-1380742025-07-18T09:45:48Z Self-Controlled Case Series Studies Farrington, Paddy Whitaker, Heather Ghebremichael-Weldeselassie, Yonas Relative Incidence;SCCS Method;case-control studies;SCCS;cohort studies;Risk Period;epidemiology;Time Invariant Covariates;exposure;MMR Vaccine;vaccinations;MMR Vaccination;drug reactions;Monte Carlo Standard Error;Heather Whitaker;Time Invariant Confounders;Yonas Ghebremichael Weldeselassie;Non-homogeneous Poisson Process;Case Crossover Method;Primary Time Line;Smoothing Parameter;Asymptotic Relative Efficiency;Hib Vaccine;Hexavalent Vaccines;Spline Model;Sample Size Formula;Data Sets thema EDItEUR::P Mathematics and Science::PS Biology, life sciences thema EDItEUR::P Mathematics and Science::PB Mathematics::PBT Probability and statistics thema EDItEUR::M Medicine and Nursing::MB Medicine: general issues::MBN Public health and preventive medicine::MBNS Epidemiology and Medical statistics thema EDItEUR::P Mathematics and Science::PS Biology, life sciences thema EDItEUR::P Mathematics and Science::PB Mathematics::PBT Probability and statistics thema EDItEUR::M Medicine and Nursing::MB Medicine: general issues::MBN Public health and preventive medicine::MBNS Epidemiology and Medical statistics Self-Controlled Case Series Studies: A Modelling Guide with R provides the first comprehensive account of the self-controlled case series (SCCS) method, a statistical technique for investigating associations between outcome events and time-varying exposures. The method only requires information from individuals who have experienced the event of interest, and automatically controls for multiplicative time-invariant confounders, even when these are unmeasured or unknown. It is increasingly being used in epidemiology, most frequently to study the safety of vaccines and pharmaceutical drugs. Key features of the book include: A thorough yet accessible description of the SCCS method, with mathematical details provided in separate starred sections. Comprehensive discussion of assumptions and how they may be verified. A detailed account of different SCCS models, extensions of the SCCS method, and the design of SCCS studies. Extensive practical illustrations and worked examples from epidemiology. Full computer code from the associated R package SCCS, which includes all the data sets used in the book. The book is aimed at a broad range of readers, including epidemiologists and medical statisticians who wish to use the SCCS method, and also researchers with an interest in statistical methodology. The three authors have been closely involved with the inception, development, popularisation and programming of the SCCS method. 2024-05-17T04:42:36Z 2024-05-17T04:42:36Z 2024-05-16T09:25:26Z 2018 book OCN: 1035389982 https://library.oapen.org/handle/20.500.12657/90263 9781032095530 9780429957512 9780429957529 9780429491313 9781498781596 https://directory.doabooks.org/handle/20.500.12854/138074 eng Chapman & Hall/CRC Biostatistics Series open access image/jpeg image/jpeg image/jpeg image/jpeg Attribution-NoDerivatives 4.0 International Attribution-NoDerivatives 4.0 International Attribution-NoDerivatives 4.0 International Attribution-NoDerivatives 4.0 International https://library.oapen.org/bitstream/20.500.12657/90263/1/9780429957536.pdf https://library.oapen.org/bitstream/20.500.12657/90263/1/9780429957536.pdf https://library.oapen.org/bitstream/20.500.12657/90263/1/9780429957536.pdf https://library.oapen.org/bitstream/20.500.12657/90263/1/9780429957536.pdf Taylor & Francis Chapman and Hall/CRC 10.1201/9780429491313 10.1201/9780429491313 fa69b019-f4ee-4979-8d42-c6b6c476b5f0 Open University 9781032095530 9780429957512 9780429957529 9780429491313 9781498781596 Chapman and Hall/CRC 377 open access |
| spellingShingle | Relative Incidence;SCCS Method;case-control studies;SCCS;cohort studies;Risk Period;epidemiology;Time Invariant Covariates;exposure;MMR Vaccine;vaccinations;MMR Vaccination;drug reactions;Monte Carlo Standard Error;Heather Whitaker;Time Invariant Confounders;Yonas Ghebremichael Weldeselassie;Non-homogeneous Poisson Process;Case Crossover Method;Primary Time Line;Smoothing Parameter;Asymptotic Relative Efficiency;Hib Vaccine;Hexavalent Vaccines;Spline Model;Sample Size Formula;Data Sets thema EDItEUR::P Mathematics and Science::PS Biology, life sciences thema EDItEUR::P Mathematics and Science::PB Mathematics::PBT Probability and statistics thema EDItEUR::M Medicine and Nursing::MB Medicine: general issues::MBN Public health and preventive medicine::MBNS Epidemiology and Medical statistics thema EDItEUR::P Mathematics and Science::PS Biology, life sciences thema EDItEUR::P Mathematics and Science::PB Mathematics::PBT Probability and statistics thema EDItEUR::M Medicine and Nursing::MB Medicine: general issues::MBN Public health and preventive medicine::MBNS Epidemiology and Medical statistics Farrington, Paddy Whitaker, Heather Ghebremichael-Weldeselassie, Yonas Self-Controlled Case Series Studies |
| title | Self-Controlled Case Series Studies |
| title_full | Self-Controlled Case Series Studies |
| title_fullStr | Self-Controlled Case Series Studies |
| title_full_unstemmed | Self-Controlled Case Series Studies |
| title_short | Self-Controlled Case Series Studies |
| title_sort | self controlled case series studies |
| topic | Relative Incidence;SCCS Method;case-control studies;SCCS;cohort studies;Risk Period;epidemiology;Time Invariant Covariates;exposure;MMR Vaccine;vaccinations;MMR Vaccination;drug reactions;Monte Carlo Standard Error;Heather Whitaker;Time Invariant Confounders;Yonas Ghebremichael Weldeselassie;Non-homogeneous Poisson Process;Case Crossover Method;Primary Time Line;Smoothing Parameter;Asymptotic Relative Efficiency;Hib Vaccine;Hexavalent Vaccines;Spline Model;Sample Size Formula;Data Sets thema EDItEUR::P Mathematics and Science::PS Biology, life sciences thema EDItEUR::P Mathematics and Science::PB Mathematics::PBT Probability and statistics thema EDItEUR::M Medicine and Nursing::MB Medicine: general issues::MBN Public health and preventive medicine::MBNS Epidemiology and Medical statistics thema EDItEUR::P Mathematics and Science::PS Biology, life sciences thema EDItEUR::P Mathematics and Science::PB Mathematics::PBT Probability and statistics thema EDItEUR::M Medicine and Nursing::MB Medicine: general issues::MBN Public health and preventive medicine::MBNS Epidemiology and Medical statistics |
| topic_facet | Relative Incidence;SCCS Method;case-control studies;SCCS;cohort studies;Risk Period;epidemiology;Time Invariant Covariates;exposure;MMR Vaccine;vaccinations;MMR Vaccination;drug reactions;Monte Carlo Standard Error;Heather Whitaker;Time Invariant Confounders;Yonas Ghebremichael Weldeselassie;Non-homogeneous Poisson Process;Case Crossover Method;Primary Time Line;Smoothing Parameter;Asymptotic Relative Efficiency;Hib Vaccine;Hexavalent Vaccines;Spline Model;Sample Size Formula;Data Sets thema EDItEUR::P Mathematics and Science::PS Biology, life sciences thema EDItEUR::P Mathematics and Science::PB Mathematics::PBT Probability and statistics thema EDItEUR::M Medicine and Nursing::MB Medicine: general issues::MBN Public health and preventive medicine::MBNS Epidemiology and Medical statistics thema EDItEUR::P Mathematics and Science::PS Biology, life sciences thema EDItEUR::P Mathematics and Science::PB Mathematics::PBT Probability and statistics thema EDItEUR::M Medicine and Nursing::MB Medicine: general issues::MBN Public health and preventive medicine::MBNS Epidemiology and Medical statistics |
| url | OCN: 1035389982 |
| work_keys_str_mv | AT farringtonpaddy selfcontrolledcaseseriesstudies AT whitakerheather selfcontrolledcaseseriesstudies AT ghebremichaelweldeselassieyonas selfcontrolledcaseseriesstudies |