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Old 08-07-2012
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Default What would an increase in a sample size change?

A study to examine the association between a suspected dietary nutrient and stomach cancer fails to find a significant association. If the investigators repeat the study with a larger sample size, in what way is this result likely to change?

a) The probability of concluding that a chance association is not statistically significant will decrease
b) The probability of concluding that a chance association is statistically significant will decrease
c) The probability of a false-negative statistical test will be greater
d) The statistical power of the study will be greater
e) The study's effect size will decrease
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Originally Posted by Casandra View Post
A study to examine the association between a suspected dietary nutrient and stomach cancer fails to find a significant association. If the investigators repeat the study with a larger sample size, in what way is this result likely to change?

a) The probability of concluding that a chance association is not statistically significant will decrease
b) The probability of concluding that a chance association is statistically significant will decrease
c) The probability of a false-negative statistical test will be greater
d) The statistical power of the study will be greater
e) The study's effect size will decrease
D- statistical power -> increasing sample size is more likely to detect false null hypothesis(type2 error)
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Yes statistical power of study will increase.
Just ready this point today somewhere.
If we flip coin 4 times then we have chances that may be we get 1 heads or 50% heads or even more. So it varies in small no. Of population drastically.
Whereas if we flip coin 10,000 times then chances of getting heads would be approx 50%.
I know it's not an ideal example but you can figure out that with change in total no. Of people stats results varies a lot.


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d is correct
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D due to PPV
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a) The probability of concluding that a chance association is not statistically significant will decrease

or

d) The statistical power of the study will be greater
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Default correct answer

The answer is d) The statistical power of the study will be greater

The power of a statistical test is the probability that a conclusion of statistical significance is correct (i.e., the probability of a true-positive result). Statistical power is determined by effect size, α level, and sample size. If the other factors remain constant, increasing sample size will increase statistical power.

As for A) - This is a true-negative result with a probability of (1 – α). α, and therefore (1 – α), is predetermined by the investigator, usually at 5%, and is not changed by increasing sample size.

As for B) - This is a false-positive result, with a probability of α. Before the study, the investigator sets the α level, usually at 5%, which is not changed by the sample size.
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Quote:
Originally Posted by Casandra View Post
The answer is d) The statistical power of the study will be greater

The power of a statistical test is the probability that a conclusion of statistical significance is correct (i.e., the probability of a true-positive result). Statistical power is determined by effect size, α level, and sample size. If the other factors remain constant, increasing sample size will increase statistical power.

As for A) - This is a true-negative result with a probability of (1 α). α, and therefore (1 α), is predetermined by the investigator, usually at 5%, and is not changed by increasing sample size.

As for B) - This is a false-positive result, with a probability of α. Before the study, the investigator sets the α level, usually at 5%, which is not changed by the sample size.
Again awesome questions casandra... keep up the good work but can you please explain option A and B more as i am not able to fully connect above explanation with given option A and B in question
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Quote:
Originally Posted by Casandra View Post
The answer is d) The statistical power of the study will be greater

The power of a statistical test is the probability that a conclusion of statistical significance is correct (i.e., the probability of a true-positive result). Statistical power is determined by effect size, α level, and sample size. If the other factors remain constant, increasing sample size will increase statistical power.

As for A) - This is a true-negative result with a probability of (1 α). α, and therefore (1 α), is predetermined by the investigator, usually at 5%, and is not changed by increasing sample size.

As for B) - This is a false-positive result, with a probability of α. Before the study, the investigator sets the α level, usually at 5%, which is not changed by the sample size.
Is there anything other than PPV and NPV that will be changed by sample size??
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