One sample binomial test?
$begingroup$
A cancer with poor prognosis, a three-year mortality of $85%$, is studied. A new mode of chemotherapy is to be evaluated. Suppose that when testing at the 0.05 significance level, one wishes to be $95%$ certain of detecting a difference if survival has been increased to $50%$ or more. The randomized clinical trial will have equal numbers of people in each group. How many patients should be randomized?
My attempt:
p = 0.85
Z = 1.96 for 0.05 significance level
As it says $95%$ sure, this implies the error cannot be more than 5% , thus Margin of error (E ) = 0.05
Thus sample size = $p * (1-p) * (Z / E)^2$
On plugging the values we get:
Sample size = $0.85*0.15*(1.96/0.05)^2$
Sample size = 195.92 = 196
Am I missing something?
statistics statistical-inference
asked Dec 9 '18 at 21:27
LadyLady
1128
$endgroup$
add a comment |
$begingroup$
A cancer with poor prognosis, a three-year mortality of $85%$, is studied. A new mode of chemotherapy is to be evaluated. Suppose that when testing at the 0.05 significance level, one wishes to be $95%$ certain of detecting a difference if survival has been increased to $50%$ or more. The randomized clinical trial will have equal numbers of people in each group. How many patients should be randomized?
My attempt:
p = 0.85
Z = 1.96 for 0.05 significance level
As it says $95%$ sure, this implies the error cannot be more than 5% , thus Margin of error (E ) = 0.05
Thus sample size = $p * (1-p) * (Z / E)^2$
On plugging the values we get:
Sample size = $0.85*0.15*(1.96/0.05)^2$
Sample size = 195.92 = 196
Am I missing something?
statistics statistical-inference
asked Dec 9 '18 at 21:27
LadyLady
1128
$endgroup$
add a comment |
$begingroup$
A cancer with poor prognosis, a three-year mortality of $85%$, is studied. A new mode of chemotherapy is to be evaluated. Suppose that when testing at the 0.05 significance level, one wishes to be $95%$ certain of detecting a difference if survival has been increased to $50%$ or more. The randomized clinical trial will have equal numbers of people in each group. How many patients should be randomized?
My attempt:
p = 0.85
Z = 1.96 for 0.05 significance level
As it says $95%$ sure, this implies the error cannot be more than 5% , thus Margin of error (E ) = 0.05
Thus sample size = $p * (1-p) * (Z / E)^2$
On plugging the values we get:
Sample size = $0.85*0.15*(1.96/0.05)^2$
Sample size = 195.92 = 196
Am I missing something?
statistics statistical-inference
asked Dec 9 '18 at 21:27
LadyLady
1128
$endgroup$
A cancer with poor prognosis, a three-year mortality of $85%$, is studied. A new mode of chemotherapy is to be evaluated. Suppose that when testing at the 0.05 significance level, one wishes to be $95%$ certain of detecting a difference if survival has been increased to $50%$ or more. The randomized clinical trial will have equal numbers of people in each group. How many patients should be randomized?
My attempt:
p = 0.85
Z = 1.96 for 0.05 significance level
As it says $95%$ sure, this implies the error cannot be more than 5% , thus Margin of error (E ) = 0.05
Thus sample size = $p * (1-p) * (Z / E)^2$
On plugging the values we get:
Sample size = $0.85*0.15*(1.96/0.05)^2$
Sample size = 195.92 = 196
Am I missing something?
statistics statistical-inference
statistics statistical-inference
asked Dec 9 '18 at 21:27
LadyLady
1128
asked Dec 9 '18 at 21:27
LadyLady
1128
asked Dec 9 '18 at 21:27
LadyLady
1128
asked Dec 9 '18 at 21:27
LadyLady
1128
asked Dec 9 '18 at 21:27
LadyLady
1128
1128
add a comment |
add a comment |
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