Evidence Based Medicine pills
Evidence Based Medicine pills
With small sample size, the variance of the Pearson’s coefficient increases, decreasing the precision of its estimates. The use of Fisher's z helps to stabilize the variance and obtain more precise estimates in meta-analyses whose outcome measure is a correlation, and when the sample of primary studies is small.
Multiple regression regularization (shrinkage) techniques can be very useful to address collinearity or overfitting problems. In addition, they can be used to select the independent variables and reduce multidimensionality, achieving more robust and easy-to-interpret models. Ridge, lasso and elastic network regression techniques are described.
The parameters that report on the quality of a multiple logistic regression model and that are usually provided by the statistical programs with which they are carried out are reviewed. Emphasis is placed on the goodness of fit, the predictive capacity and the statistical significance of the model.
The parameters that report on the quality of a multiple linear regression model and that are usually provided by the statistical programs with which they are carried out are reviewed. Emphasis is placed on the goodness of fit, the predictive capacity and the statistical significance of the model.
The sample size necessary to estimate the comparison of two means depends on the confidence level of the estimate, the power of the study, the variability of the measured variable and the magnitude of the difference that is to be detected.