The primary advantage of proportional hazards regression over simply comparing survival curves is to be able to consider the case when the hazard ratio between the two groups is not constant (proportional) over time. be able to evaluate a binary outcome variable. allow for the consideration of factors other than just treatment group on the time to the event of interest. be able to compute a hazard ratio and associated 95% confidence interval.

Survival Analysis This technique is used to analyze the time that is an event variable that reflects…

Answered: The primary advantage of proportional…

MATLAB: An Introduction with Applications

6th Edition

ISBN:9781119256830

Author:Amos Gilat

Publisher:Amos Gilat

Chapter1: Starting With Matlab

Section: Chapter Questions

Problem 1P

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Your company is evaluating two cloud-based secured data storage services. "Great Sky," the newer service, claims its uploading and downloading speeds are faster than the older service, "Clear and Steady Skies." You need to make a decision based on published access times for both services at different times and for varying file sizes. To make your decision, you purchase two statistical studies from which you discover the average download time for Great Sky is 0.67 sec. per MB and for Clear Steady Skies is 0.84. Additionally, the studies indicate the following sample information: NGS = 60 ncss = 50, SGS = 0.25 and scss = 0.55. Use a .05, and the five step hypothesis testing procedure to make the appropriate decision. Prepare an Excel worksheet properly labeled and well formatted to share with your boss (a very picky person that truly appreciates good looking work product).
Baseball statisticians studied how often triples (a certain event in a baseball game) occurred in professional games played between 1947 and 2017. A 98 percent confidence interval to estimate the slope of the linear regression line relating the year, x, and the mean number of triples per game, y, yielded (−0.006,−0.002). A check shows that the conditions necessary for inference for the slope of the regression line are met.
According to some theorists, teenagers who spend more time with their friends in unsupervised activities are more likely to engage in delinquent conduct. You question a random sample of 2,500 high-school youths about number of hours spent in unsupervised peer activities (e.g., cruising, shopping, movies) and frequency of delinquent behavior. Unit of analysis/observation = Population = Sample = %3D Dependent variable = * Level of measurement: Independent variable = Level of measurement:
On minitab or excel Calculating the coefficient of determination of a set of data, it was obtained that r^2 = 0.845 . Based on this value, it can be concluded that: Options: The least squares line provided a good fit as a large proportion of the variability in "y" has been explained by the least squares line. The least squares line provided a good fit as a small proportion of the variability in "y" has been explained by the least squares line. The least squares line did not provide a good fit since a small proportion of the variability in "y" has been explained by the least squares line. The least squares line did not provide a good fit since a large proportion of the variability in "y" has been explained by the least squares line.
If the coefficient B₁ has a nonzero value, then it is helpful in predicting the value of the response variable. If B₁ = 0, it is not helpful in predicting the value of the response variable and can be eliminated from the regression equation. To test the claim that B₁ = 0 use the test statistic t = (b₁-0) /sp. Critical values or P-values can be found using the t distribution with n - (k+1) degrees of freedom, where k is the number of predictor (x) variables and n is the number of observations in the sample. The standard error sp, is often provided by software. For example, see the accompanying technology display, which shows that sp=0.076885101 (found in the column with the heading of "Std. Err." and the row corresponding to the first predictor variable of height). Use the technology display to test the claim that B₁ = 0. Also test the claim that B₂ = 0. What do the results imply about the regression equation? Click the icon to view the technology output. Test the claim that B₁ = 0. For…
(d) At the 0.05 level of significance, is there evidence of a linear relationship between the number of cases delivered and the delivery time? (e) Construct a 95% confidence interval estimate of the population slope β1. Interpret the confidence interval estimate. (f) How useful do you think this regression model is for predicting the delivery times?
Does the confidence interval support the claim that the mean impact strength of gears from supplier 2 is at least 25 foot-pounds higher than that of supplier 1?

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		be able to consider the case when the hazard ratio between the two groups is not constant (proportional) over time.
		be able to evaluate a binary outcome variable.
		allow for the consideration of factors other than just treatment group on the time to the event of interest.
		be able to compute a hazard ratio and associated 95% confidence interval.