Showing papers on "False positive paradox published in 1989"

Avoiding false positives with PCR

Abstract: The exquisite sensitivity of the polymerase chain reaction means DNA contamination can ruin an entire experiment. Tidiness and adherence to a strict set of protocols can avoid disaster.

Context-based automated detection of epileptogenic sharp transients in the EEG: elimination of false positives

Abstract: A description is given of a knowledge-based system for the elimination of false positives in the automated detection of epileptogenic sharp transients in the EEG (electroencephalogram). The system makes comprehensive use of spatial and temporal context information available on 16 channels of EEG. EKG, (electrocardiogram) EMG (electromyogram), and EOG (electrooculogram). A knowledge-based implementation is used because of the ease with which it allows the contextual rules to be expressed and refined. The resulting system is shown to be capable of rejecting a wide variety of artifacts commonly found in EEG recordings that cause numerous false positive detections in systems making less comprehensive use of context. >

If at First You Don't Succeed Setting Passing Scores When More Than One Attempt Is Permitted:

Abstract: For licensing and certification examinations designed to protect the public, passing incompetent candidates (false positives) is a more serious error than failing competent ones. Yet to avoid classification mistakes against individuals and subsequent litigation, current practices for these tests increase the relative risk of false positives. These practices are identified, and one that allows positive errors of measurement arising from multiple opportunities to pass the test is discussed in detail. Unsatisfactory ways to mitigate this problem are considered. Increasing the amount of testing or, if that is not feasible, raising the required passing score for repeaters is recommended.

Joint Estimation of Incidence and Diagnostic Error Rates from Irregular Longitudinal Data

Abstract: Longitudinal studies often involve the repeated diagnosis across time of each patient's status with respect to a progressive categorical process. When the occurrence of a change in status is not readily apparent, two factors can make modeling and assessing the incidence rates of progression difficult. First, because diagnoses may be difficult, they may not be performed with the frequency necessary to pinpoint exact times of incidence. Second, uncertainty in the diagnostic process can obscure identification of the time interval in which incidence occurs. When serial diagnoses are fallible, even small error rates can seriously disrupt interpretation and make using the aforementioned methods difficult or impossible. For example, if false diagnoses (both false positives and negatives) occur independently with probability .05 in a longitudinal study involving four serial diagnoses, 19% of the strings of serial diagnoses would be expected to contain at least one error. If the underlying process is prog...

Honesty testing: Estimating and reducing the false positive rate

Abstract: Bayes' theorem was used to provide a realistic estimate of the false positive rate in honesty testing. Separate estimates were provided for employee theft and production deviance. Examples were used to illustrate how follow-up screening procedures can significantly reduce either the false positive or false negative rate. Suggestions were provided for how test developers can capitalize on research in the area of honesty testing to develop alternative methods of identifying dishonest applicants.

Screening for possible human carcinogens and mutagens. False positives, false negatives: statistical implications.

Abstract: A screening method aimed at identifying potential human carcinogens using either animal cancer bioassays or short-term genotoxic assays has 4 possible results: true positive, true negative, false positive and false negative. Such a categorisation is superficially similar to the results of hypothesis testing in a statistical analysis. In this latter case the false positive rate is determined by the significance level of the test and the false negative rate by the statistical power of the test. Although the two types of categorisation appear somewhat similar, different statistical issues are involved in their interpretation. Statistical methods appropriate for the analysis of the results of a series of assays include the use of Bayes' theorem and multivariate methods such as clustering techniques for the selection of batteries of short-term test capable of a better prediction of potential carcinogens. The conclusions drawn from such studies are dependent upon the estimates of values of sensitivity and specificity used, the choice of statistical method and the nature of the data set. The statistical issues resulting from the analysis of specific genotoxicity experiments involve the choice of suitable experimental designs and appropriate analyses together with the relationship of statistical significance to biological importance. The purpose of statistical analysis should increasingly be to estimate and explore effects rather than for formal hypothesis testing.

Can parents do a throat culture

Abstract: Throat swabs for Group A beta-hemolytic Streptococcus were obtained from 98 patients, ages 4 to 17 years, both by their parents and by physician investigators. Compared with results obtained by physicians, there was a false negative rate of 32% (P less than 0.001) for the parents. The discrepancy was greater in the youngest age group (38% false negative rate in the 4- to 8-year-olds) compared with older children (P less than 0.001). The overall sensitivity and negative predictive value for the parent-obtained swabs were 68 and 45%, respectively. In the 4- to 8-year-old group, these values were 62 and 37%, respectively. Because there were no false positives the positive predictive value was 100%. We conclude that the false negative rate for untrained parents obtaining throat swabs is too high to warrant the implementation of home testing for Group A streptococci.

Radiological examination of the small bowel.

Abstract: A retrospective study was made of 100 consecutive dedicated per-oral small bowel examinations. 33% of the studies were abnormal, of which almost half were due to Crohn's disease. When grouped according to clinical suspicion, 73.5% of those studies with a high index of clinical suspicion were abnormal. In the abnormal group a correct diagnosis was made in 90%, with two false positives. In the normal group a correct diagnosis was made in 91%, with no false negatives. It is suggested that the dedicated small bowel series offers a justifiable and practical alternative to other techniques such as intubation and direct infusion of contrast medium into the small bowel, or enteroclysis.

Nonrandom distribution of genotypes among red cell indices.

Abstract: Venous blood samples were obtained from 25,302 healthy adults in Kentucky, USA. The red cell indices measured on these samples were evaluated by multiple stepwise regression analysis to derive an algorithm capable of discriminating the 138 individuals within this population who had genotypes AA, AC, AS or AA beta-thalassemia. The simple discriminant MCV2 x MCH with a cut-off set at 1530 detected 137 out of 138 of the heterozygotes with a false positive rate in this population of 4.4%. Other discriminants tested produced fewer false positives but also missed a sufficient number of heterozygotes to be unacceptable for genetic counselling purposes.

A Neural Network to Detect Homologies in Proteins

Abstract: In order to detect the presence and location of immunoglobulin (Ig) domains from amino acid sequences we built a system based on a neural network with one hidden layer trained with back propagation. The program was designed to efficiently identify proteins exhibiting such domains, characterized by a few localized conserved regions and a low overall homology. When the National Biomedical Research Foundation (NBRF) NEW protein sequence database was scanned to evaluate the program's performance, we obtained very low rates of false negatives coupled with a moderate rate of false positives.

Sensitivity, Specificity, and Predictive Values in the 'Sensitivity and Specificity of Clinical Diagnostics'

Abstract: To the Editor.— The article concerning postmortem evaluation of clinical diagnostics during five decades1is a good effort to analyze disparate data that can be resistant to marshaling by ordinary statistical methods. However, I think that the true-negative category, within the constraints of this study, is largely a passive statistic that sheds little light on the diagnostic process. This occurs because the act of making a clinical diagnosis leads to a mutually exclusive binomial distribution of that diagnosis vs a statistical universe of other diagnoses, many of which are trivial. On the other hand, "agreed" (true positives), "underdiagnosed" (false negatives), and "overdiagnosed" (false positives) are intuitively satisfying categories that present a more realistic picture of actual practice. Another statistical method avoids the true-negative dilemma by using only those cells of the fourfold (2 × 2) tables that can be occupied by at least one positive diagnosis (clinical or autopsy).

Sensitivity, Specificity, and Predictive Values in the 'Sensitivity and Specificity of Clinical Diagnostics'

Abstract: To the Editor.— There was a confusing explanation of sensitivity and specificity in the article by Anderson et al 1 in the March 17 issue. Assuming proper use of the terms true positives, true negatives, false positives , and false negatives , sensitivity and specificity are defined correctly in the "Methods" section and in the footnote to Table 1. However, it appears that the correct positions of false negatives and false positives were switched in Table 1 (Table). This distinction is important, because if the data for all subsequent tables were analyzed as described in the published Table 1, then what is reported as the sensitivity is actually the predictive value of a positive, and the reported clinical accuracy of a positive diagnosis is actually the sensitivity. A similar switch would also have occurred with the specificity and the clinical accuracy of a negative diagnosis.