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Methodology Series Module 1: Cohort Studies
Cohort design is a type of nonexperimental or observational study design. In a cohort study, the participants do not have the outcome of interest to begin with. They are selected based on the exposure status of the individual. They are then followed over time to evaluate for the occurrence of the ou...
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Formato: | Online Artículo Texto |
Lenguaje: | English |
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Medknow Publications & Media Pvt Ltd
2016
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Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4763690/ https://www.ncbi.nlm.nih.gov/pubmed/26955090 http://dx.doi.org/10.4103/0019-5154.174011 |
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author | Setia, Maninder Singh |
author_facet | Setia, Maninder Singh |
author_sort | Setia, Maninder Singh |
collection | PubMed |
description | Cohort design is a type of nonexperimental or observational study design. In a cohort study, the participants do not have the outcome of interest to begin with. They are selected based on the exposure status of the individual. They are then followed over time to evaluate for the occurrence of the outcome of interest. Some examples of cohort studies are (1) Framingham Cohort study, (2) Swiss HIV Cohort study, and (3) The Danish Cohort study of psoriasis and depression. These studies may be prospective, retrospective, or a combination of both of these types. Since at the time of entry into the cohort study, the individuals do not have outcome, the temporality between exposure and outcome is well defined in a cohort design. If the exposure is rare, then a cohort design is an efficient method to study the relation between exposure and outcomes. A retrospective cohort study can be completed fast and is relatively inexpensive compared with a prospective cohort study. Follow-up of the study participants is very important in a cohort study, and losses are an important source of bias in these types of studies. These studies are used to estimate the cumulative incidence and incidence rate. One of the main strengths of a cohort study is the longitudinal nature of the data. Some of the variables in the data will be time-varying and some may be time independent. Thus, advanced modeling techniques (such as fixed and random effects models) are useful in analysis of these studies. |
format | Online Article Text |
id | pubmed-4763690 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2016 |
publisher | Medknow Publications & Media Pvt Ltd |
record_format | MEDLINE/PubMed |
spelling | pubmed-47636902016-03-07 Methodology Series Module 1: Cohort Studies Setia, Maninder Singh Indian J Dermatol IJD® Module on Biostatistics and Research Methodology for the Dermatologist Cohort design is a type of nonexperimental or observational study design. In a cohort study, the participants do not have the outcome of interest to begin with. They are selected based on the exposure status of the individual. They are then followed over time to evaluate for the occurrence of the outcome of interest. Some examples of cohort studies are (1) Framingham Cohort study, (2) Swiss HIV Cohort study, and (3) The Danish Cohort study of psoriasis and depression. These studies may be prospective, retrospective, or a combination of both of these types. Since at the time of entry into the cohort study, the individuals do not have outcome, the temporality between exposure and outcome is well defined in a cohort design. If the exposure is rare, then a cohort design is an efficient method to study the relation between exposure and outcomes. A retrospective cohort study can be completed fast and is relatively inexpensive compared with a prospective cohort study. Follow-up of the study participants is very important in a cohort study, and losses are an important source of bias in these types of studies. These studies are used to estimate the cumulative incidence and incidence rate. One of the main strengths of a cohort study is the longitudinal nature of the data. Some of the variables in the data will be time-varying and some may be time independent. Thus, advanced modeling techniques (such as fixed and random effects models) are useful in analysis of these studies. Medknow Publications & Media Pvt Ltd 2016 /pmc/articles/PMC4763690/ /pubmed/26955090 http://dx.doi.org/10.4103/0019-5154.174011 Text en Copyright: © Indian Journal of Dermatology http://creativecommons.org/licenses/by-nc-sa/3.0 This is an open access article distributed under the terms of the Creative Commons Attribution-NonCommercial-ShareAlike 3.0 License, which allows others to remix, tweak, and build upon the work non-commercially, as long as the author is credited and the new creations are licensed under the identical terms. |
spellingShingle | IJD® Module on Biostatistics and Research Methodology for the Dermatologist Setia, Maninder Singh Methodology Series Module 1: Cohort Studies |
title | Methodology Series Module 1: Cohort Studies |
title_full | Methodology Series Module 1: Cohort Studies |
title_fullStr | Methodology Series Module 1: Cohort Studies |
title_full_unstemmed | Methodology Series Module 1: Cohort Studies |
title_short | Methodology Series Module 1: Cohort Studies |
title_sort | methodology series module 1: cohort studies |
topic | IJD® Module on Biostatistics and Research Methodology for the Dermatologist |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4763690/ https://www.ncbi.nlm.nih.gov/pubmed/26955090 http://dx.doi.org/10.4103/0019-5154.174011 |
work_keys_str_mv | AT setiamanindersingh methodologyseriesmodule1cohortstudies |