Bias,Validity偏差有效性.ppt

1、Medical Research: Validity, Bias, Confounds, Probability, P-value, and Power,Kimberly Pendell,Validity,Validity implies that the measurement reliably measures what it intends to measure. Validity relates to the magnitude of bias.,Bias,Bias is the systematic tendency to produce an outcome that differ

2、s from the underlying truth.,Some different types of bias,Selection bias Interviewer bias Recall bias Detection bias Verification bias Publication bias,Bias and Research Designs,Confounds,A confound is a variable that is distributed differently in the study group and the control group and that affec

3、ts the outcome being assessed. (Riegelman, 2005) Confounding variables can appear through bias or random chance.,Probability,Probability is the quantitative estimate of the likelihood of condition existing (as in a diagnosis) or of subsequent events (such as in a treatment study). (Guyatt, Rennie, 2

4、002),P-value,P-value is the probability of an outcome occurring by chance. The p-value establishes statistical significance. In medical research the standard p-value is p.05,Power,Power is the ability of a research study to demonstrate statistical significance. Researchers determine the size of stud

5、y population needed for a set amount of power before beginning their study. If the study has statistically significant results, the study has enough power. In medical research the standard for power is 80%.,Readings:,Guyatt, G., Rennie, D. (Eds.). (2002). Users guide to the medical literature: a manual for evidence-based practice. USA: American Medical Association. Katzer, J., Cook, K.H., Crouch, W.W. (1998). Evaluating information: a guide for users of social science research. Massachusetts: McGraw Hill. Riegelman, R.K. (2005). Studying a study & testing