Sentence examples for inadequate random from inspiring English sources

Figure 2 shows the forest plot of the differences in ES between trials with adequate and inadequate random sequence generation.

We hope that "unclear" random is less risk of selection bias than that of definitely "inadequate" random.

Inadequate random sequence generation and blinding could result in selection bias, as patients with worse visual prognoses might be offered the combination treatment.

For example, inadequate random assignment of HIV-infected persons could result in more advanced immunosuppression among those in the isoniazid group and thus a higher probability of resistance.

Therefore, one of the predefined subgroup analyses of trials with adequate versus inadequate random sequence generation, allocation concealment, and blinding could not be done.

There was no statistically significant difference between the ES of trials with adequate or inadequate random sequence generation (ES=0.02; 95% CI −0.12 to 0.15).

To test the robustness of significant results, sensitivity analyses were conducted for studies with high or unclear risk of selection bias (inadequate or unclear random sequence generation and/or allocation concealment) versus low risk of selection bias (adequate random sequence generation and/or allocation concealment).

While the response of reinforcing steel beyond the elastic phase is described through yielding, hardening, softening, and fracture under monotonic loading, these monotonic parameters are inadequate to incorporate random cyclic effects such as strength degradation because steel is vulnerable to fatigue damage under seismic loads.

We excluded quasi-randomised trials, as these have a high risk of bias owing to the inadequate method of random sequence generation or allocation concealment.

It remains to be determined whether they are truly specific to rhizomes or due to inadequate sampling in random sequencing of transcriptomes.

Inadequate reporting of random allocation, allocation concealment, blinding, intention-to-treat analysis, and dropout accounts in the majority of trials may have led to performance bias and detection bias since the patients and researchers were aware of therapeutic interventions for the subjective outcome measures.