ling
Forum Senior
Topics: 23
Posts: 46
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A 1-year study of a new drug to treat hypertension is conducted. One hundred patients with hypertension are enrolled; 50 patients are given the new drug and another 50 patients are given hydrochlorothiazide. All patients completed the trial. One noted unexpected effect is increased growth of scalp hair which occurred in those taking the new drug, a nonstatistically significant difference (p>0.10). This effect has also been reported in studies of other similar drugs in the new therapeutic class. The investigators of the study concluded that the new drug did not cause hair growth. Which of the following features of this study is most likely to affect the validity of this conclusion?
A
) Differential follow-up
B
) Lead time bias
C
) Length of the study
D
) Sample size
E
) Self-selection
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| robin082006
Forum Hero
Topics: 471
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D) Sample size
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| maiya
Forum Newbie
Topics: 3
Posts: 35
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can anyone explain this?!!! these questions drive me nuts - these are probably the "easy points" if you can decipher the language...anyone got any tricks for these?!!!
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| r_albayunen
Forum Senior
Topics: 0
Posts: 218
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D
the greater the sample size .. the greater the statistical significance
i think .. 
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| fongch
Forum Elite
Topics: 71
Posts: 316
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A possible problem w/ the conclusion stated is a type 2 error, which is most likely caused by small sample size (and therefore low statistic power).
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| NE
Forum Guru
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Posts: 504
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P>0.10 means low power of the study and MCC of this kind of study is too small sample size!
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| krisrama
Forum Newbie
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the test results are not statistically significant. it failed to detect the difference (between the drug in question and other drugs, when in fact a difference might have existed). In other words, the power is low. This could be due to small sample size.
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| Drtweetie
Forum Elite
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Posts: 301
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Agree with (D)--small sample size
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| bariluis
Forum Junior
Topics: 11
Posts: 39
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There is no information about the randomization. If not randomized, one of the main threats to validity is the selection bias, referred as 'self-slection' here. If you have a selection bias, even a bigger sample size will not produce statistically significant and meaningul p-value.
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