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Biostatistics Controlling for biases72 Controlling for biases72

Bias refers to systematic errors that result from the way the study was designed, executed, or interpreted

Common sources of bias in clinical trials include

 Lack of (or failure in) randomization, leading to unbalanced groups

  •  Patients in each group should not be significantly different demographically and with respect to medications, comorbidities, medical histories, etc.

Poor blinding, leading to unfair treatment and biased assessments

Large numbers of patients lost to follow-up

Bias must be assessed before CIs can be interpreted

Even very large samples and very narrow CIs can be misleading if the studies were biased

Bias refers to systematic errors that result from the way the study was designed, executed, or interpreted

Common sources of bias in clinical trials include

Lack of (or failure in) randomization, leading to unbalanced groups

 Patients in each group should not be significantly different demographically and with respect to medications, comorbidities, medical histories, etc.

Poor blinding, leading to unfair treatment and biased assessments

Large numbers of patients lost to follow-up

Bias must be assessed before CIs can be interpreted

Even very large samples and very narrow CIs can be misleading if the studies were biased

Jump to:

p-value Confidence interval Limitations Effect size NNT & NNH

Controlling for biases

References

70. Flechner L, Tseng TY. Understanding results: P-values, confidence intervals, and number needed to treat. Indian Journal of Urology. 2011;27(4):532-535.
71. Davies HTO, Crombie IK. What are confidence intervals and p-values? April 2009. Available at http://www.bandolier.org.uk/painres/download/whatis/What_are_Conf_Inter.pdf.
72. Citrome L, Ketter TA. When does a difference make a difference? Interpretation of number needed to treat, number needed to harm, and likelihood to be helped or harmed. Int J Clin Pract. 2013;67(5):407–411.