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Increasing the specificity of the test lowers the probability of type I errors, but raises the probability of type II errors (false negatives that reject the alternative hypothesis when it is true).
OSullivan, Jack W; Albasri, Ali; Nicholson, Brian D; Perera, Rafael; Aronson, Jeffrey K; Roberts, Nia; Heneghan, Carl (11 February 2018)."False Positive" redirects here.An example for a false negative is a test indicating that a woman is not pregnant whereas she is actually pregnant.I thought being HIV positive is a death sentence but the Thai doctors said having diabetes is much worse than having an HIV which is now a manageable disease." loved it and came back weekly specifically for a session with it!I am getting the best medication for very low price which is Atripla and I am undetectable after 2 months of therapy.



The latter is known as the false positive risk (see Ambiguity in the definition of false positive rate, below ).
"The reproducibility of research and the misinterpretation of p-values".
It wouldn't even reach the 5 percent level.
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