Sentence examples for reliable study design from inspiring English sources

Exact(3)

Prospective observational design is generally considered a more reliable study design than a cross-sectional design.

It is a reliable study design to evaluate possible risk factors.

To grasp the opportunity to develop more effective therapy in malignant glioma incorporating Temozolomide will require robust and reliable study design coupled with intellectually honest interpretation of results.

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This confirms findings from several studies with less reliable study designs during the last years [9, 23, 24], but contrast with an earlier population-based study, which did not find an association between previous head injury and headache [12].

This marks the evaluation among other treatment groups for a less comparative analysis to the untreated defect denoting the rabbit model relatively less reliable to our study design.

To come to conclusions based on reliable data, an impeccable study design and long-term follow-up are crucial.

However, this heterogeneity among the case control studies may serve to highlight the less reliable nature of case control study design as it inherently involves recall bias since dietary information is collected after disease development.

In the longer, cancer, studies the small number of events in the three prospective studies (one of which [ 15] had information only on deep infection) meant that no reliable estimate of effects of study design could be made (Table 3).

The aim of our paper is to explore the relative impact of these parameters on sample size computation and to identify the most relevant to be used during study design for reliable power determination for Rasch models.

Overall, the findings show that the hydroponic study design allows for reliable quantification of plant uptake over a range of compound/crop combinations.

Reliable methods for predicting delta during study design and better reporting of the basis for these predictions are needed to minimize the risk of trial failure from type II statistical errors and resulting waste of research resources.

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