LECTURE 06 2011

LECTURE 06 2011 - Outline of Stratification Lectures...

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Outline of Stratification Lectures Definitions, examples and rationale (credibility) Implementation Fixed allocation (permuted blocks) Adaptive (minimization) Rationale - variance reduction
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Stratification A procedure in which factors known to be associated with the response (prognostic factors) are taken into account in the design (e.g., randomization) Pre-stratification refers to a stratified design; post-stratification refers to the analysis
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Pre- versus Post Stratification and Precision (Variance Reduction) As a general rule, the precision gained with pre- versus post-stratification is less than one might expect The gain in precision is greatest in small studies (where you need it the most) because the risk of chance imbalance is greater. Covariate adjustment for prognostic factors is usually carried out with regression (e.g., linear, logistic, or proportional hazards regression.
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Stratification Can Increase Precision Simple versus stratified random sampling. Snedecor and Cochran note (p. 520): “If we form strata so that a heterogeneous population is divided into parts each of which is fairly homogeneous, we may expect a gain in precision over simple random sampling”. Ref. Snedecor and Cochran, Statistical Methods
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Stratification Can Increase Precision Randomized block versus completely random design. Snedecor and Cochran note (p. 299): “Knowledge (about predictors or response) can be used to increase the accuracy of experiments. If there are a treatments to be compared,…first arrange the experimental units in groups of a , often called replications. The rule is that units assigned to the same replication should be as similar in responsiveness as possible. Each treatment is then allocated by randomization to one unit in each replication…Replications are therefore usually compact areas of land…This experimental plan is called randomized blocks.”
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Pre-stratification Does Not Matter. Peto et al note: “As long as good statistical methods, …,are used to analyze data from clinical trials, there is no need for randomization to be stratified by prognostic features.” Keep it simple so investigators are not discouraged from participating. Post-stratified analysis is needed with pre-
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This note was uploaded on 11/21/2011 for the course PUBH 7420 taught by Professor Ph7420 during the Spring '07 term at Minnesota.

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LECTURE 06 2011 - Outline of Stratification Lectures...

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