Interpretation of longitudinal studies. An overview.
Interpretation of longitudinal studies. An overview.
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纵向研究的解释。
DOI:
--
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发表时间:
1996
影响因子:
24.7
通讯作者:
Ira B. Tager
中科院分区:
文献类型:
--
作者:
Jan P. Schouten;Ira B. Tager
In their introductory overview, Weiss and Ware (1) list six advantages of longitudinal research. Three of these seem particularly important in relation to interpretation and, to some extent, these three subsume the other strengths: (1) understanding the temporal order of events; (2) observation of individual patterns of change; and (3) assessment of both level and change. The latter of the three is a variation of the first two, since the linkage between process (change) and state (level)depends upon a clear understanding of the temporal sequence. It is perhaps trite to note that all of these characteristics of longitudinal studies are interrelated. However, the emphasis on one or another of these elements usually determines the study design and analysis and defines the duration of time and the place in the natural history of a disease or a process over which inference is appropriate. The former point is highlighted by Sherrill and Viegi's(2) distinction between time seriesprocedures (focus on the individual's response over time) and longitudinal procedures when group mean trends are of interest. Dockery and Brunekreef (3) make the latter point particularly clear in their presentation. In this paper, we briefly summarize the various ways that studies have focused on these three elements. We discuss the strengths of the approaches with regard to interpretation of the "longitudinal" characteristics of the design and the intended inference, and wediscuss the benefits of inference from longitudinal studies versus those that can be made from cross-sectional designs. Since there is general agreement that specification of proper temporal sequence is a sine qua non as a criterion for valid causal inference in epidemiologic (observational) studies (4, 5), we discuss temporal sequence only in terms of the time frame over which inference is relevant for specific types of studies. Finally, we confine our discussion to applications for continuous data, since the major thrust of longitudinal epidemiologic analysis of lung function is in this direction (in contrast to discrete classifications such as "diseased"/"nondiseased").
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影响因子:
2
作者:
Rosner,B;Muñoz,A;Tager,I;Speizer,F;Weiss,S
通讯作者:
Weiss,S
DOI:
10.1164/arrd.1982.125.5.544
发表时间:
1982
期刊:
The American review of respiratory disease
影响因子:
--
作者:
Glindmeyer,HW;Diem,JE;Jones,RN;Weill,H
通讯作者:
Weill,H
DOI:
10.1164/ajrccm/154.6_pt_2.s223
发表时间:
1996
期刊:
American journal of respiratory and critical care medicine.
影响因子:
--
作者:
Wypij,D
通讯作者:
Wypij,D
DOI:
10.1164/arrd.1984.130.3.380
发表时间:
1984
期刊:
The American review of respiratory disease
影响因子:
--
作者:
Higgins,MW;Keller,JB;Landis,JR;Beaty,TH;Burrows,B;Demets,D;Diem,JE;Higgins,IT;Lakatos,E;Lebowitz,MD
通讯作者:
Lebowitz,MD
DOI:
10.1164/ajrccm/154.6_pt_2.s217
发表时间:
1996
期刊:
American journal of respiratory and critical care medicine.
影响因子:
--
作者:
Sherrill,D;Viegi,G
通讯作者:
Viegi,G