In statistics, epidemiology, marketing and demography, a cohort is a group of subjects who share a defining characteristic (typically subjects who experienced a common event in a selected time period, such as birth or graduation).
Cohort data can oftentimes be more advantageous to demographers than period data. Because cohort data is honed to a specific time period, it is usually more accurate. It is more accurate because it can be tuned to retrieve custom data for a specific study.
In addition, cohort data is not affected by tempo effects, unlike period data. On the contrary, cohort data can be disadvantageous in the sense that it can take a long amount of time to collect the data necessary for the cohort study. Another disadvantage of cohort studies is that it can be extremely costly to carry out, since the study will go on for a long period of time, demographers often require sufficient funds to fuel the study.
Demography often contrasts cohort perspectives and period perspectives. For instance, the total cohort fertility rate is an index of the average completed family size for cohorts of women, but since it can only be known for women who have finished child-bearing, it cannot be measured for currently fertile women. It can be calculated as the sum of the cohort's age-specific fertility rates that obtain as it ages through time. In contrast, the total period fertility rate uses current age-specific fertility rates to calculate the completed family size for a notional woman, were she to experience these fertility rates through her life.
A study on a cohort is a cohort study.
Two important types of cohort studies are:
Prospective Cohort Study: In this type of study, there is a collection of exposure data (baseline data) from the subjects recruited before development of the outcomes of interest. The subjects are then followed through time (future) to record when the subject develops the outcome of interest. Ways to follow-up with subjects of the study include: phone interviews, face-to-face interviews, physical exams, medical/laboratory tests, and mail questionnaires.
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vignette|350px thumb|350px|Nombre d'années (en rouge) pour que la population mondiale augmente d'un milliard d'individus. Ce type de diagramme inclut à la fois une dimension d'évaluation démographique rétrospective et une part de prospective démographique (projections démographiques pour la période 2010/2050). Le chiffre entre parenthèses indique l'année à laquelle le seuil du milliard d'êtres humains est atteint La démographie est l'étude quantitative et qualitative des caractéristiques des populations et de leurs dynamiques, à partir de thèmes tels que la natalité, la fécondité, la mortalité, la nuptialité (ou conjugalité) et la migration.
thumb|right|400px|Carte indiquant l' espérance de vie à la naissance dans les États membres de l'ONU en 2007. L'espérance de vie humaine est un des indicateurs statistiques les plus utilisés dans le domaine de la prospective et des projections démographiques, et pour évaluer le niveau de développement et l'indice de développement humain d'un État ou d'une région du monde. Elle permet de quantifier les conditions de mortalité à une année donnée : l'espérance de vie à la naissance est égale à la durée de vie moyenne d'une population fictive qui vivrait toute son existence dans les conditions de mortalité de l'année considérée.
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Background: Although digital mobility outcomes (DMOs) can be readily calculated from real-world data collected with wearable devices and ad-hoc algorithms, technical validation is still required. The aim of this paper is to comparatively assess and validat ...
The study of regional trends in the rural-urban fertility gradient helps us to understand the pace of completion of the fertility transition and the geography of urban growth in the global South. We question whether the hypothesized inverted U-shaped evolu ...
2019
We use a combination of extreme value statistics, survival analysis and computer-intensive methods to analyse the mortality of Italian and French semi-supercentenarians. After accounting for the effects of the sampling frame, extreme-value modelling leads ...