역학 연구에서의 스터디 디자인

역학 연구에서의 스터디 디자인

역학 연구에서의 스터디 디자인을 한 눈에 볼 수 있는 테이블이다. 각각의 스터디 디자인에서 기술 연구, 분석 연구를 할 때 일반적으로 어떤 measure를 사용하는지, 그리고 스터디 디자인마다 장, 단점은 무엇인지 파악할 수 있다.

Table 1: Main study designs in classic epidemiology.

Case reports Case series Ecological studies Cross sectional studies Case control Cohort Intervention trials Unit of study (Single case)  individual (>1 cases) individual Population Individual Individual Individual Individual Description Describes unusual characteristics of a case A group of cases Comparing populations in different places at the same time or, in a time series Study of population at, “point-in-time,” Study of two groups of subjects: (case; disease of interest and control; disease-free) Study of two groups of subjects (exposure and non-exposure groups) Study and examine two groups of subjects (intervention and control groups) Direction Present Present Present Present Reverse Forward Forward Type of measurement Reporting, description Reporting, description Correlation Prevalence, association Odds ratio Prevalence, incidence, relative risk, attributable risk Prevalence, incidence, relative risk, attributable risk Advantages Quick, having clinical importance, opportunities for physicians to exchange of thoughts Quick, having clinical importance, opportunities for physicians to exchange of thoughts Quick, inexpensive, group-level studies may also be the only way to study the effects of group-level constructs, for example, laws Easy, inexpensive, useful for investigating fixed exposures such as blood group, most convenient in outbreaks of disease Relatively inexpensive good for rare diseases Efficient in resources and time Better for rare exposures, ability to determine causality relations The strongest evidence for causality, control of unknown confounders, fulfils the basic assumption of statistical hypothesis tests limitation Inability to determine statistical relations and analysis Inability to determine statistical relations and analysis Ecological fallacy Susceptible to selection bias and misclassification, difficult to establish a putative, “cause”, Not good for rare diseases or rare exposures Susceptible to selection bias and misclassification bias, may be difficult to establish that, “cause,” preceded effect Costly and time consuming, susceptible to selection bias. Relatively statistically inefficient unless disease is common. Expensive, time consuming, sometimes ethically generalizability problem

https://www.hindawi.com/journals/isrn/2013/952518/tab1/