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#1
08-16-2012
 USMLE Forums Master Steps History: Step 1 Only Posts: 864 Threads: 62 Thanked 370 Times in 224 Posts Reputation: 380
Confidence Interval

The IQ scores are obtained from a sample of 100 patients diagnosed with various types of schizophrenia who completed a standard IQ test battery. An additional 20 patients had to be dropped from the sample because they lacked the functional capacity to complete two or more portions of the test. Four other patients refused to take the test battery when offered the opportunity. Results for the patients who completed the test battery gave an average IQ of 110 and a standard deviation of 20.
Using this information. Compute the 95% confidence interval for this estimate of the mean.

A. 70 to 130
B. 70 to 150
C. 85 to 115
D. 90 to 130
E. 105 to 115
F. 106 to 114
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 The above post was thanked by: Kabutar111 (08-16-2012), venky2600 (08-16-2012)

#2
08-16-2012
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B. 70 to 150

Mean +/- 2SD
#3
08-16-2012
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F

nice one
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#4
08-16-2012
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yup you are right - the answer should be F. 106 to 114

I totally misread this question - somehow my mind read it "in which brackets 95% of patients will be"
#5
08-16-2012
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why ??

why it is f ???
please anyone put the law you use to make calculations ???
#6
08-16-2012
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Quote:
 Originally Posted by Casandra yup you are right - the answer should be F. 106 to 114 I totally misread this question - somehow my mind read it "in which brackets 95% of patients will be"
😉 that's why I said nice one ,I was looking for 108 n 112 in beginning

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#7
08-16-2012
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Quote:
 Originally Posted by good fire why it is f ??? please anyone put the law you use to make calculations ???
Use full formula including standard error

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#8
08-16-2012
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This is from Kaplan Qbank.

#9
08-17-2012
 USMLE Forums Master Steps History: Step 1 Only Posts: 864 Threads: 62 Thanked 370 Times in 224 Posts Reputation: 380

formula used
confidence interval= mean +_ Z(S/square root of sample no. (N)
where
Z= standard score, for 95% its 2(approx) and for 99% its 2.58 (2.5 or 2.6 for calculation purpose)
S= standard deviation.

In this question N would be 100 (as we don't exclude those who later on left the study for some or other purpose)
110+_ 2 (20/square root of 100)
answer= 110 +_ 4 = 106 - 114.

Now my question: So is it a general rule that we have to consider whole sample of people without considering people who left study or not.
Won't it will be any kinda bias. May be "volunteer screwed my study kinda bias"
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#10
08-17-2012
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Quote:
 Originally Posted by koolkiller88 Now my question: So is it a general rule that we have to consider whole sample of people without considering people who left study or not. Won't it will be any kinda bias. May be "volunteer screwed my study kinda bias"
Well it depends. In this question, you consider everyone who finished the trial because that's what the question asked you. But, as in this case, this data might not give you a true picture of whats going on.
To give a different example of this question, lets say we're testing a certain drug X for patients with multiple sclerosis. Out of 1000 people initially enrolled in the treatment arm of the trial, 400 drop out due to disabling, but nonlethal side effects(lets say severe malaise, body aches). Only 600 people finish the trial and at the end of the trial, the relapse rate in this population is found to be significantly lower than the control arm(standard of care).

If you only consider the population that finished the study(what we call Per-protocol analysis) you'll be able to present data showing that the drug works and is actually a good one. BUT when you actually look at the everyone who participated(this is called Intention to Treat analysis), you'll find that people dropped out, and for a very significant reason!! This drug will probably not be prescribed by many physicians unless they have no choice.
Bottomline is that data in a drug trial can be presented in a favourable way. Thats why its always important to look at the exact numbers, not just the %s given in an abstract.
 The above post was thanked by: checcles (08-17-2012), koolkiller88 (08-17-2012), sruthi (08-17-2012)

 Tags Biostatistics-Epidemiology, Step-1-Questions

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