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Old 02-06-2012
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Q. A randomized, double-blind clinical trial was conducted to compare the efficacy of two antifungal drugs for treating a common dermatological problem. All participants in the study had been previously diagnosed with the fungal infection. Half of the study participants received a newly developed antifungal agent and half received the commonly prescribed alternative. The sample size was selected to provide a statistical power of 70%. Results of the study showed that the fungus disappeared in 50% of the patients receiving the newer agent and in 40% of patients receiving the alternative treatment. Results of the study stated p = .13. Using the commonly accepted alpha criterion, the chance that the study results will not reflect the results of the treatment for this type of fungus in the population at large is which of the following?
A. 0
B. .10
C. .13
D. .30
E. .70
F. .87
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Old 02-06-2012
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Ans .....C ....... alpha reflect P , so less that 13% chance that the study will not be effective .....
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Old 02-06-2012
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if p=0.13,fail to reject the nulll hypothesis i.e decide that the drug does not work

if p=0.02 (less then 0.13) ,reject the null hypothesis,i.e decide that drug works.

thats why i will go with answer (C)
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I will go with C too
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Old 02-08-2012
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The answer is D.
This question asks for the probability of Type II or beta error. The computed p-value of .11 is greater than the common alpha criterion of p ¡Ü .05, therefore we do not reject the null hypothesis. When we fail to reject the null hypothesis the chance of a Type I error is zero, however, a Type II error is a distinct possibility. Because the p-value is about Type I error, it is not the key for answering question. Instead, recall that Type II error is related to statistical power in the following manner: 1 ¨C Power = Type II error. In this case statistical power is given at 70%, therefore: 1- .70 = .30. No, choice A is the chance of a Type I error in the presented case. No, choice B is the difference between the 50% and the 40% results for the two anti-fungal drugs. It gives us a sense of clinical significance, but nothing about the chance of Type II error. No, choice C is the computed p-value, which is greater than p < .05, meaning we cannot reject the null hypothesis. It tells us Type I error IF we did reject, but does not tell us the chance of Type II. Choice E is the statistical power, as given in the question. 1 ¨C power = beta. Choice F is derived by 1 - .13 =.87 but does not give the chance of Type II error. Simply if .13 is the chance of being wrong if we reject the null hypothesis (Type I error), then .87 is the chance of being right if we reject the null hypothesis. Type II error is the chance of being wrong if we do NOT reject the null hypothesis.
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