Comparaciones múltiples en diseños transversales con datos dependientes

Abstract

Multiple comparisons in cross-sectionals designs with dependent data. The assumption of independence of observations may seem like a reazonable assumption in examinimi data cross-sectional using experimental designs of single-factor. The assumption of independence, however is seldom verified by the investigators. By this reason we pretend to examine the relationship between true Types I and II error probabilities under the effects of departures from independence assumptions on hypothesis testing in six multiple comparison procedures.