Chapter 12--Multisample Inference

For example a nal answer to a research question

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Unformatted text preview: ysis of Variance (ANOVA) Multiple Comparisons The Kruskal-Wallis Test Two-Way ANOVA Introduction Simultaneously testing more than one hypothesis among the treatment means. For example, a final answer to a research question depends on the results from more than one comparison. We need to understand how the error rate of the individual comparisons influence the error rate applicable to the overall conclusions The comparisons could be pre-planned or post-hoc. The assumptions needed are the same as before. Chapter 12: Multisample Inference Stat 491: Biostatistics Analysis of Variance (ANOVA) Multiple Comparisons The Kruskal-Wallis Test Two-Way ANOVA Post-Hoc Comparisons Hypothesis generated after looking at the data. If H0 : µ1 = µ2 = · · · = µk is rejected, we would like to know in what way the means differ. which treatment is the best, second best,... if there is an increasing trend in the mean. We can do post-hoc comparisons if we account for the after the fact nature of the hypothesis. generate hypothesis but no inference with the current data. Chapter 12: Multisample Inference Stat 491: Biostatistics Analysis of Variance (ANOVA) Multiple Comparisons The Kruskal-Wallis Test Two-Way ANOVA Contrasts among Treatment Means The quantity = a1 µ1 + a2 µ2 + . . . + ak µk = ai µi with the coefficients satisfying ai = 0 is called a linear contrast between treatment means. Examples: Suppose we have k = 5 treatments with mean responses µ1 ,µ2 ,µ3 ,µ4 and µ5 . (a) (b) (c) (d) 1 2 3 4 = µ1 − µ2 = 1 (µ2 + µ4 ) − 1 (µ3 + µ5 ) 2 2 = 1 (µ1 + µ2 ) − 1 (µ3 + µ4 + µ5 ) 2 3 = 3µ1 + 3µ2 + (−2)µ3 + (−2)µ4 + (−2)µ5 Contrasts 3 and 4 are equivalent. Comparisons can be stated as linear contrasts. Chapter 12: Multisample Inference Stat 491: Biostatistics Analysis of Variance (ANOVA) Multiple Comparisons The Kruskal-Wallis Test Two-Way ANOVA Contrasts among Sample Means Contrast among sample means ˆ= ai yi . ¯ are used to estimate the corresponding contrast among treatment means = ai µ i . The estimated variance for a contrast among sample means is 2 ˆ V ( ˆ) = sW Chapter 12: Multisample Inference ai2 /ni . Stat 491: Biostatistics Analysis of Variance (ANOVA) Multiple Comparisons The Kruskal-Wallis Test Two-Way ANOVA An Example The reduction in systolic blood pressure (BP) after a drug for hypertension is administered is one of key indicators of how well the patient is responding to the drug. When treating for hypertension, the side effects associated with the drug are of particular concern. In a study, two drugs A and B for reducing the side effects of a standard hypertension drug S were evaluated. Drugs A and B were administered concurrently with drug S. The study was conducted using a completely randomized design, with five treatments, as Treatment Drug 1 Standard (S) 2 S combined with low dose of A (S+AL) follows: 3 S combined with high dose of A (S+AH) 4 S combined with low dose of B (S+BL) 5 S combined with high dose of B (S+BH) Chapter 12: Multisample Inference Stat 491: Biostatistics Analysis of Variance (ANOVA) Mu...
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This note was uploaded on 02/03/2014 for the course STAT 491 taught by Professor Solomonharrar during the Fall '12 term at Montana.

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