Epidemiological research analysis of previous studies

An example already discussed is the large county-based ecologic study in which a decrease in lung cancer mortality was observed in association with increased radon exposure in sharp contrast to the increase expected from current knowledge Cohen, All cancer registries in the United States use classification schemes that are largely compatible with each other and with the classification for causes of death on death certificates.

Statistical and epidemiological analyses of data

In the analogue of that scenario, times as many i. An example of systematic error is if, unknown to you, the pulse oximeter you are using is set incorrectly and adds two points to the true value each time a measurement is taken. Conclusions you draw based on that data will still be incorrect. The cumulative incidence is also often interpreted as the risk that an individual develops a specified disease within a period in time. Standardized incidence ratios SIR or standardized mortality ratios SMR are used for comparison with the general population. However, for cancers that are not commonly fatal, for example, thyroid cancer, the most useful end point of disease burden is incidence of the disease since in any given year mortality will represent both new and existing cases of disease. One way to assess the validity of findings is the ratio of false-positives claimed effects that are not correct to false-negatives studies which fail to support a true effect. In Spain, we do not have access to ideal epidemiologic studies of stroke. The lag time between exposure to a disease-causing agent such as ionizing radiation and the clinical recognition of the disease is known as the latency period.

Suppose that, given the mean dose in some underpowered low-dose study, the expected true RRs for a series of health outcomes were about 1. However, if the frequency of these errors is not large, and not different in exposed versus unexposed areas, the random misclassification should have little effect on the identification of any increased risk.

Systematic error[ edit ] A systematic error or bias occurs when there is a difference between the true value in the population and the observed value in the study from any cause other than sampling variability. There is usually an uneasy balance between the need for adequate precision and the practical issue of study cost.

data analysis of epidemiological studies

Bias, on the other hand, is not reduced by simply increasing sample size in the absence of other improvements; if larger samples mean that less attention can be given to quality of the individual observations, bias may even increase with sample size.

A 40 percent increase in risk could be detected with 4 to 8 years of accrual for the to matched studies see Table 4. The primary site of a cancer is more likely to be recorded accurately by a cancer registry than a death certificate German et al.

Comparison of the study findings regarding the risks in a population using a pure proximity approach to those from an analysis that incorporates reconstruction of the doses received by the same population can prove informative.

In contrast, Marrugat et al1 moved in the opposite direction as they assumed the MBDS draws on such a wide catchment area that it guarantees adequate selection.

What are the factors that could and should be examined to help detect and adjust for possible confounding such as smoking and exposure to medical diagnostic procedures? Since approximately 15 percent of these women 6, are expected to live within 50 km of nuclear facilities this means that it would take around years of follow-up to detect an excess risk of 20 percent for this cancer, under the same assumptions as above.

This article has been cited by other articles in PMC.

statistics used in epidemiology
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Data Analysis of Epidemiological Studies