PubMed Health⌕ Search

PubMed · 3446290

Logistics of a multinational population study.

Abstract

The shaping of epidemiology as a clinical science prompted the perpetuation of large scale population studies aimed to determine causality and assessment of new therapeutical modalities. In order to achieve meaningful conclusions one has to rely on large masses of data, assembled by several teams of investigators in multi-geographical localities. The larger the number and diversity of participating groups, the more complex are the methodology and the final interpretation of outcome. A number of key principles in the undertaking of a long term joint population study are pointed out along 6 study stages: contemplation, planning, organization, data collection, analysis and outcome. The hypothesis has to be clearly formulated, financial resources mobilized, and lines of authority and communications strictly defined, before onset. Subsequently, the step by step routine of monitoring of the individual satellite centers, quality control and budget allocation, have to be established. The interpretation of the data may become final stumbling block since outcome is dependent on the quality of input and may be influenced by preconceived ideas of the investigators. Finally, the cooperative spirit behind the study may disappear once personalities and interests change. Hence, the future ownership of the data should be agreed upon before the conglomerate of data is split and fragmentated.

Explore related subjects

Keep this discovery

Explore connections, maps & timelines

BibTeXRIS

B Modan. 1987. Logistics of a multinational population study.. https://pubmed.ncbi.nlm.nih.gov/3446290/

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related citations

Probability estimation when some observations are grouped.

This paper considers the use of additional questions for decreasing survey non-response rates and an approach for estimating a probability based on the results obtained. In a survey, the respondents are asked to answer an original question and follow-up questions, where the answers for the follow-up questions are grouped answers for the original question. For example, respondents are asked to provide an exact number of incidents, but in cases of 'Do not know' or 'Refuse' responses, they are subsequently asked to pick an answer from a less specific categorical scale. The new estimator obtains smaller variance asymptotically and does not depend on a distribution family. This method is applied to income questions in a survey regarding injury prevention and behaviours. Another application is survey data on intimate partner violence, where some amendments were applied for incorporating post-stratification weights and for using non-random grouping. For additional illustration, an example of parameter estimation on artificially generated data is presented.

Data Collection↗