![]() It is very important to select a method that will produce interpretable and valid results for your study. Many procedures have been proposed for the random assignment of the participants to treatment groups in clinical trials.Ĭommon randomization techniques includes, simple randomization, block randomization, stratified randomization, and covariate adaptive randomization, are reviewed.Įach method is described along with its advantages and disadvantages. In such instances, random assignment is essential and guarantees validity for the statistical tests of significance that are used to compare treatments. Thus, the ideal way of balancing covariates among groups is to apply sound randomization in the design stage of the clinical research (before the adjustment procedure) as an alternative of the post data collection. The adjustment needed for each covariate group may vary, which is difficult because ANCOVA uses the average slope across the groups to adjust the outcome variable. One of the critical assumptions in ANCOVA is that the slopes of the regression lines are the same for each group of the covariates. On the other hand, the interpretation of this post adjustment approach is often difficult because imbalance of the covariates regularly leads to unanticipated interaction effects, such as unequal slopes among subgroups of covariates. Statistical techniques such as analysis of covariance (ANCOVA), multivariate ANCOVA, or both, are often used to adjust for covariate imbalance in the analysis stage of the clinical research. The outcome of the research can be negatively influenced by this insufficient randomization. Schul and Grimes stated that trials with insufficient or unclear randomization tended to overestimate treatment effects up to 40% compared with those that used proper randomization. Knowledge of the group assignment creates a layer of potential selection bias that may taint the data. That is, researchers, subject or patients or participants, and others should not know to which group the subject will be assigned. Second, proper randomization ensures no former knowledge of group assignment (i.e., allocation concealment). The effects of the treatment would be identical from the influence of the imbalance of covariates, thereby requiring the researcher to control for the covariates in the analysis in order to obtain an unbiased result. If a greater proportion of the older subjects are assigned to the treatment group, then the result of the surgical intervention may be influenced by this imbalance. ![]() Suppose that subjects are assigned to control and treatment groups in a study investigating the effectiveness of a surgical intervention. Within a clinical research, if patient groups are significantly different, research results will be biased. Researchers in life science research demand randomization for a number of reasons.įirst, topics in different groups do not vary in any systematic way. transforming data stream (such as when using a scrambler in telecommunications). ![]()
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