Is false discovery rate the same as P value?

The false discovery rate is the complement of the positive predictive value (PPV) which is the probability that, when you get a ‘significant’ result there is actually a real effect. So, for example, if the false discovery rate is 70\%, the PPV is 30\%.

What is the relationship between P value and probability?

A p-value is a measure of the probability that an observed difference could have occurred just by random chance. The lower the p-value, the greater the statistical significance of the observed difference. P-value can be used as an alternative to or in addition to pre-selected confidence levels for hypothesis testing.

Is the P value the probability that the null hypothesis is false?

The p-value is the probability that the null hypothesis is true. (1 – the p-value) is the probability that the alternative hypothesis is true. A low p-value shows that the results are replicable. A non-significant result, leading us not to reject the null hypothesis, is evidence that the null hypothesis is true.

How do you use false discovery rate?

For example, if the PPV was 60\% then the false discovery rate would be 40\%. The image below shows a medical test that accurately identifies 90\% of real diseases/cases. The false discovery rate is the ratio of the number of false positive results to the number of total positive test results.

What does the p-value mean in regression?

The p-value for each term tests the null hypothesis that the coefficient is equal to zero (no effect). A low p-value (< 0.05) indicates that you can reject the null hypothesis. Conversely, a larger (insignificant) p-value suggests that changes in the predictor are not associated with changes in the response.

Can P value be misleading?

Whether intentional or not, there is a tendency for p-values to devolve into a conclusion of “significant” or “not significant” based on whether the p-value is less than or equal to 0.05. This can be very misleading. Conversely, an effect can be large, but fail to meet the p<0.05 criterion if the sample size is small.

How reliable is p value?

Reality: A single p value gives you a very uncertain prediction about repeatability, and it is unable to estimate the value of a repeat experiment. Any obtained p values can only be valid in the sample from which they are calculated.

Is it true to say the p-value measures the probability that the null hypothesis is true why or why not?

Nope. The P value is computed assuming that the null hypothesis is true, so cannot be the probability that it is true. P values cannot tell you whether this assumption is correct. P value tells you how rarely you would observe a difference as larger or larger than the one you observed if the null hypothesis were true.