Chapter 11 Notes

Chapter 11 Notes - Chapter 11 Analyzing Complex Designs...

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1 Chapter 11 Analyzing Complex Designs Overview – Example r Review of Chapter 9 r Experiments typically involve more than two levels of the IV r Example: Weight loss c 53 obese individuals randomized to 5 conditions • Reward • Punishment • Both reward and punishment • Monitor with neither reward nor punishment • No monitoring (control group)
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2 Overview – Example r To analyze this data we could 10 t- tests c Means for group 1 vs group 2 c Means for group 1 vs group 3 c Etc. .. r There is a problem here The Problem of Multiple Tests r Remember that the alpha (.05) level relates to the risk of making a Type I Error r The alpha level refers to a single test r Type I error increases as we perform a greater number of tests The Problem of Multiple Tests r If our alpha level was set at .05 and we conducted 100 different t-tests we would erroneously see reject the null hypothesis for 5 tests c With t-tests the more we conduct, the more likely we are to make a Type I error
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3 The Problem of Multiple Tests r The probability of making a Type I error is 1 – (1 – alpha) c c C = the number of tests c Weight loss example • 1- (1- .05) 10 = .40 Preventing Type I Error r You can prevent Type I error inflation by using the Bonferoni adjustment:
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Chapter 11 Notes - Chapter 11 Analyzing Complex Designs...

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