false negative error

false negative error

Type II error Statistics An error which occurs when the statistical analysis of a trial detects no difference in outcomes between a treatment group and a control group when in fact a true difference exists
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This susceptibility to prevalence occurs logically because the probability of making a false positive decision error is lower where the prevalence of true positives is higher, and the probability of making a false negative error is lower when the prevalence of true negatives is greater.
Detecting more true positives (the same as decreasing false negative errors and increasing sensitivity) always comes at a cost to increased false positive errors.
In this light a rational decision maker following accepted risk management principles would have to consider, among other things, the respective consequences of a false positive and a false negative error.
Measurements were based on True Positive and True Negative hit rates, and False Positive and False Negative error rates.
False negative errors occur when the underlying unobserved truth is different from zero effect.
All false negative errors (missed SNPs) of the 1248 centered cases are listed according to background sequence, product size, and SNP type in Table 1.
False negative errors are more serious than false positive errors because intrusions are going undetected.
Developing a nursing home PAS which minimizes both false positive and false negative errors is particularly difficult.
Company representatives presented results of a multi-center clinical trial that show that ThinPrep Pap tests yield a 4 to 1 reduction in false negative errors when compared to conventionally prepared slides made from the same patient sample.