¡Descarga Understanding Confidence Intervals and p-Values in Clinical Trials y más Resúmenes en PDF de Estadística solo en Docsity! What are confidence intervals and p-values? Presented by: Daniela Alexandra Mateus Ruiz - Code: 71167 Confidence intervals this time used for the mean of the effect of a treatment shows the range within which the actual effect of the treatment is likely to lie. p = probability of trials by chance p-values are used for confidence intervals as they indicate the range of possible effect sizes compatible with the data. P= cut point P =<0.05 When a confidence interval has non-different values between treatments it indicates that it is not significantly different from the control in general, these confidence intervals help to interpret data from clinical trials by placing upper and lower limits on was on the probable size of real effects. Bias must be assessed to interpret results but when at very narrow intervals there is most likely error small studies often report that they are neither significant nor significant about one in 20 significant findings will be false. Measurement of effect size The objective of clinical trials is to generate knowledge about the efficacy of health interventions, clinical research implies the estimation of a parameter, in this case the effect size, Size can be measured in relative risk reduction emphasizing potential benefits and absolute risk reduction providing the overall summary of potential benefits, Either of the two works if the study findings are correctly interpreted, it provides a point estimate of the effect and the question arises, is it likely that the findings of this sample are also true in other similar groups of patients? Itis very important to evaluate and bias but it is also important to focus on evaluating the role of chance, bias means any systematic error that results Most common effects in treatment trials + Lack of randomisation generating unbalanced groups + Few dismissal + Loss of patients during follow-up The effects of chance are significant once the cessation has been excluded. Random variability The results will always vary simply by chance; therefore, tools are necessary to help evaluate the differences that occur between treatments and to know if the manifestations of random variability are important or not the confidence intervals and p-values help this. What is p-values The p-value allows evaluating whether the findings are significantly different or not significantly different from some reference value What are confidence intervals Confidence intervals provide a Range over the size of the observed range. This Range allows us to know how likely itis to capture the size of the true effect; in itself it is a Range of values for a variable of interest constructed from so that this Range has a specific probability of including the true value of the variable. Specific probability = confidence level Interval end points = confidence limits Confidence intervals are constructed at the 95% level in that if the confidence interval provides a range of its position of the true effect of the treatment, the confidence intervals help us to easily know if the statistical significance or not. If the interval reflects “no effect” it is not statistically significant if the interval does not include the value that reflects “no effect” itis statistically significant. The upper and lower limits of the confidence intervals give us the information on how big or small the true effect could be, if the confidence interval is narrow, we can be quite sure that the study has been ruled out any effect far from this Range. If the confidence interval is quite wide, we can say that the study was probably small. The difference between
