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Dictionary of Evidence-based Medicine.pdf

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156 <strong>Dictionary</strong> <strong>of</strong> <strong>Evidence</strong>-<strong>based</strong> <strong>Medicine</strong><br />

drug classes, they can be predicted with reasonable degrees <strong>of</strong> certainty<br />

(Park K, Pirmohamed M, Kitteringham NR (1992) Idiosyncratic drug<br />

reactions: a mechanistic evaluation <strong>of</strong> risk factors. British Journal <strong>of</strong> Clinical<br />

Pharmacology and Therapeutics. 34: 377-95).<br />

Type D adverse reaction<br />

This term is sometimes used to describe carcinogenicity and teratogenicity.<br />

There is usually a long delay between drug exposure and appearance <strong>of</strong><br />

the adverse effect (Park K, Pirmohamed M, Kitteringham NR (1992) Idiosyncratic<br />

drug reactions: a mechanistic evaluation <strong>of</strong> risk factors. British<br />

Journal <strong>of</strong> Clinical Pharmacology and Therapeutics. 34: 377-95).<br />

Type I error<br />

In hypothesis testing this is the probability <strong>of</strong> rejecting the null hypothesis<br />

when it is in fact true. This is a false-positive rate since it gives the probability<br />

<strong>of</strong> erroneously pronouncing a test significant. This error rate is <strong>of</strong>ten<br />

called the a error rate. Conventionally, the a rate in hypothesis testing is<br />

<strong>of</strong>ten set at 0.05 (Li Wan Po A (1998) Statistics for pharmacists. Blackwell<br />

Science, Oxford).<br />

Type II error<br />

In hypothesis testing the type II error is the probability <strong>of</strong> failing to detect<br />

an effect when it is in fact present. This error rate is <strong>of</strong>ten referred to as the<br />

p error. The complement <strong>of</strong> type II error (1-P) is called the power <strong>of</strong> the test.<br />

Conventionally, the (3 error is <strong>of</strong>ten set at 0.8.

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