Primary Outcomes [edit] Arterial Thromboembolism 0.4% vs. 0.3% (P=0.01 for noninferiority; P=0.73 for superiority) Stroke: 0.2% vs. 0.3% TIA: 0.2% vs. 0% Systemic Embolism: 0% vs. 0% Major bleeding 1.3% vs. 3.2% (P=0.005 for superiority; NNH=50) Secondary Outcomes [edit] The remaining p-values are for superiority. All-cause mortality 0.5% vs. 0.4% (P=0.88) Myocardial Infarction 0.8% vs. 1.6% (P=0.10) Deep-vein Thrombosis 0% vs. 0.1% (P=0.25) Pulmonary Embolism 0% vs. 0.1% (P=0.25) Minor Bleeding 12.0% vs. 20.9% (P<0.001)
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- production of urc acid in the body can be an indication of cell breakdown. This may be an advance indication of illness such as gout, leukemia, or lymphoma over the period of thirteen months The mean concentrations was X = 5.33 mg/dI. The distribution of uric acid in healthy adult males can be assumed to be normal, with a =1.75 mg/di.Briefly discuss how ANCOVA is different from ANOVA.A patient screens positive for Disease Y. The screener has a sensitivity of 60%. The best next step for the patient is most likely: Start treatment for Disease Y Get a diagnostic test Take a different screening test None of these are correct.
- Positive autocorrelation in control charts has which of the following characteristics? A. Is observed when large values follow large values B. Can cause high false-negative rates for special cause variation C. Is seen when large values follow small values D. Is a rare occurrence with measurements of a same patient or provider over timeTreatment 1 Treatment 2 Treatment 3 n = 10 n = 10n = 10 N = 30 T= 10 T = 20T = 30 G = 60 SS = 27 SS = 16 SS = 23 EX2 = 206 A study comparing three different treatment conditions is summarized above. Is there a significant difference between any of the treatment groups?Ankle Brachial Index. The ankle brachial index (ABI) compares the blood pressure of a patient’s arm to the blood pressure of the patient’s leg. The ABI can be an indicator of different diseases, including arterial diseases. A healthy (or normal) ABI is 0.9 or greater. In a study by M. McDermott et al. titled “Sex Differences in Peripheral Arterial Disease: Leg Symptoms and Physical Functioning” (Journal of the American Geriatrics Society, Vol. 51, No. 2, pp. 222–228), the researchers obtained the ABI of 187 women with peripheral arterial disease. The results were a mean ABI of 0.64 with a standard deviation of 0.15. At the 1% significance level, do the data provide sufficient evidence to conclude that, on average, women with peripheral arterial disease have an unhealthy ABI?
- In a regression, p value of an effect is 0.001, less than the level of significance (alpha = 0.05). This means that (choose all that apply) o The effect is significant o Its coefficient is not zero o The effect can be ignored o Its coefficient is zeroindicator for gender (=1 if male, =0 if female). Your data set has 200 observations. donation = 1.57 + 0.12age + 0.08age? – 0.43 gender + 0.07(gender * age), R? = 0.33 (0.15)* (0.67) (0.11) (0.01) (0.06) donation = 1.59 (0.68) 0.46 gender, R² = 0.30 (0.17) 1. Assuming homoscedastic errors, test the hypothesis that age affects charitable donations at the 5% level. 2. Interpret the coefficient on gender interacted with age. 3. How would you test that the difference in giving between men and women is independent of age? If you can run the test, run it. If you cannot, explain what you need.Acid rain A study of the effects of acid rain on trees inthe Hopkins Forest shows that 25 of 100 trees sampledexhibited some sort of damage from acid rain. This rateseemed to be higher than the 15% quoted in a recent Environmetrics article on the average proportion of dam-aged trees in the Northeast. Does the sample suggest that trees in the Hopkins Forest are more susceptible thantrees from the rest of the region? Comment, and write upyour own conclusions based on an appropriate confidence interval as well as a hypothesis test. Include any assump-tions you made about the data.
- Raw data in the table below come from an independent-measures experiment comparing three different treatment conditions. Treatment 1 0 1 0 3 X=1 Treatment 2 1 4 1 2 X=2 To evaluate the effect of the independent variable, researchers conducted the independent-measures one-way ANOVA. They computed the sum of squares between groups to be 15.5 and the sum of squares within groups 14.75. In the study, the percentage of total variability explained by the independent variable is approximately: O 0 95 49 O 51 Treatment 3 3 3 4 5 X=3.75Overproduction of uric acid in the body can be an indication of cell breakdown. This may be an advance indication of illness such as gout, leukemia, or lymphoma.f Over a period of months, an adult male patient has taken seven blood tests for uric acid. The concentration was x = 5.35 mg/dl. The distribution of uric acid in healthy adult males can be assumed to be normal, with o = 1.77 mg/dl. (a) Find a 95% confidence interval for the population mean concentration of uric acid in this patient's blood. What is the margin of error? (Round your answers to two decimal places.) lower limit upper limit margin of error (b) What conditions are necessary for your calculations? (Select all that apply.) O o is unknown O normal distribution of uric acid O n is large Oo is known O uniform distribution of uric acid (c) Interpret your results in the context of this problem. O The probability that this interval contains the true average uric acid level for this patient is 0.05. O The probability that…Effectiveness of Hypnotism in Reducing Pain. A study was conducted to measure the effectiveness of hypnotism in reducing pain. The measurements are in centimeters on a pain scale before and after hypnosis. Assume normality assumption is satisfied for this case. Use a 0.025significance level to test the the effectiveness of hypnotism in reducing pain. The two samples are dependent/matched. So you need to find the differences first, the calculated the mean and the standard deviation of the differences D = 2.05, sD = 1.524. Before 8.9 3.3 7.6 9.6 10.6 8.3 7.3 7.2After 5.9 2.7 7.2 8.8 8.9 6.6 3.6 2.7Difference 3.0 0.6 0.4 0.8 1.7 1.7 3.7 4. a. State the null and alternative hypotheses. b. List the correct critical value(s) and calculate the test statistic. c. What is your conclusion based on the test statistic and the critical value(s) obtained part (b)?