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Miguel Delgado Rodríguez

Publications and source records attributed to Miguel Delgado Rodríguez.

3 recordsLinked to original sources

[Contributions of systematic review and meta-analysis to public health].

Meta-analysis has several precedents; even in Confucius (VI BC) one can find a sentence about the synthesis of knowledge. Meta-analysis is a consequence of the paradigm of induction. Within this paradigm of research, meta-analysis gives an analysis of the principle of consistency of a causal association (2nd principle of Hill). It has promoted the development of evaluation questionnaires and protocols for different designs, mainly clinical trials. It favoured the movement of evidence-based medicine, which is behind the creation of agencies for the evaluation of health technologies, and the recognition of public health professionals dedicated to research methods (mainly epidemiologists). The contributions of meta-analysis to public health are not distinguishable from others made to other specialties, although in the field of research methods it has contributed to the study of publication bias and to the search of determinants of heterogeneity, the lack of consistency among the individual studies.

Humans↗

[Longitudinal studies: concepts and particularities].

In this review the definition of "longitudinal study" is analysed. Most current textbooks on epidemiology do not define a longitudinal study, whereas statistical textbooks do. It is more common to talk about longitudinal data than about longitudinal studies. A longitudinal study implies the existence of repeated measurements (more than two) across follow-up. According to these ideas, a longitudinal study can be considered a subtype of cohort study that, in contrast with life-table cohort studies, allows inference to the subject level, to analyze changes in variables (exposures and outcomes) and transitions among different health states. The characteristics of this design force to paid special attention to quality control during data collection, losses during follow-up, and missing data in some measurements. The statistical analysis should take repeated measures into account, and it is what finally gives the longitudinal character to a study with repeated measurements.

Biomedical Research↗