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PubMed1976

Multiple testing for the detection of B virus antibody in specially handled rhesus monkeys after capture from virgin trapping grounds.

Eight groups of rhesus monkeys totaling over 1,000 animals were captured in the virgin trapping grounds of Jammu and Kashmir, India. Individual caging and special handling technics were utilized to prevent cross-contamination during capture, holding, and subsequent shipment to quarantine facilities in the United States. Immediately following the arrival of the monkeys, 5 consecutive blood samples were obtained at approximately 2-wk intervals, and the sera were rested for neutralizing antibody against Herpesvirus simiae. In order to assure the greatest sensitivity possible, sera were not heat-inactivated and were tested against only 10 TCID50 units of virus in addition to the more commonly used concentration of 100 TCID50 units. The first test detected 80-90% of the positive animals within each group, and only 1 seroconversion was noted after the second test. Seventy-three percent of the adults, 36.6% of the young adults, and 12.4% of the juvenile macaques were found to be antibody-positive. Considering the measures employed to prevent cross contamination, these percentages probably reflect the true prevalence of B virus infection in these rhesus monkeys at the time of their capture in the wild.

Animals↗
PubMed1996

Multiple test procedures for dose finding.

The problem of identifying the lowest dose level for which the mean response differs from that at the zero dose level is considered. A general framework for stepwise testing procedures that use contrasts among the dose level means is proposed. Using this framework, several new procedures are derived. These and some existing procedures, including that of Williams (1971, Biometrics 27, 103-117; 1972, Biometrics 28, 519-531), are compared analytically and by an extensive simulation study for the normal theory balanced one-way layout case. It is pointed out that the procedures based on the so-called step and basin contrasts proposed by Ruberg (1989, Journal of American Statistical Association 84, 816-822) have excessively high type I familywise error rates (FWEs) and, hence, they should not be used. Some findings of the simulation study are as follows: For monotone dose mean configurations, Williams' procedure and two step-down test procedures based on Helmert and linear contrasts offer the best performance. For nonmonotone dose mean configurations, the performance of Williams' procedure does degrade somewhat, but the other two procedures are still the best. For more complex designs, a simple step-down test procedure that uses any alpha-level tests (not necessarily t-tests) to compare each dose level with the zero dose level controls the FWE and is the only alternative available, but its power is rather low, especially under nonmonotone configurations. Step-up procedures are generally dominated by step-down procedures when the same contrasts are used although the differences are not great.

Animals↗
PubMed2005

The positive and negative consequences of multiple-choice testing.

Multiple-choice tests are commonly used in educational settings but with unknown effects on students' knowledge. The authors examined the consequences of taking a multiple-choice test on a later general knowledge test in which students were warned not to guess. A large positive testing effect was obtained: Prior testing of facts aided final cued-recall performance. However, prior testing also had negative consequences. Prior reading of a greater number of multiple-choice lures decreased the positive testing effect and increased production of multiple-choice lures as incorrect answers on the final test. Multiple-choice testing may inadvertently lead to the creation of false knowledge.

Choice Behavior↗
PubMed1992

Maintenance of wakefulness test and multiple sleep latency test. Measurement of different abilities in patients with sleep disorders.

The multiple sleep latency test and the maintenance of wakefulness test were administered on the same day to 258 consecutive patients whose clinical presentation required evaluation for excessive sleepiness. While the MSLT is the standard test for assessing excessive daytime sleepiness, the MWT may have some clinical advantage over the MSLT when the assessment of daytime alertness is the primary goal. To explore further the relationship between alertness and sleepiness, we have conducted a thorough analysis of the similarities, differences, and correlations between MWT and MSLT. The results of this study show that the coefficient of correlation between MSLT and MWT (r = 0.41), although statistically significant, accounts for less than 17 percent of the variability between the two tests. Factor analysis suggests that two factors, alertness and sleepiness, account for 91 percent of all variance. Our data demonstrate that patients with diagnosable disorders of excessive somnolence may be discordant on the two tests (eg, having low sleep latency on MSLT but high sleep latency on MWT). Specifically, we found that some patients with abnormally low MSLT scores were able to stay awake when asked to do so on the MWT, and conversely, some patients who failed to stay awake when asked to do so on the MWT were unable to fall asleep quickly on the MSLT. We conclude that the MWT and MSLT measure different abilities and that the MWT may be a useful adjuvant daytime test in many clinical situations.

Adult↗
PubMed2001

Properties of multiple intersection-union tests for multiple endpoints in combination therapy trials.

We consider intersection-union tests involving multiple endpoints in a combination drug trial, for which we control the familywise error rate in the strong sense using closed testing methods. Bonferroni-Holm, Simes-Hommel, and Resampling-Based methods all are considered in this context. Familywise error rate control heuristics are developed and evaluated using a simulation study that is specifically tailored to the intersection-union setting. Both Resampling-Based and Simes-Hommel uniformly outperform the Bonferroni-Holm. Using simulations of power, the choice of Simes-Hommel versus Resampling-Based is seen to depend on the particular alternative of interest. Because it is simpler and has generally good power, we recommend the Simes-Hommel intersection-union tests. The techniques are illustrated using real data from a clinical trial to evaluate a combination asthma therapy.

Algorithms↗
PubMed2004

Season of birth effect on personality in a general population.

Seasonality of births in schizophrenia and other mental disorders has been consistently observed. This may be through effects of unknown environmental factors that seasonally fluctuate on the brain development. The effects may affect cognitive function of the brain and behavioral characteristics that might be correlated with the development of personality not only in patients with mental disorders but also in healthy subjects. We, therefore, investigated the effects of season of birth on personality traits in healthy Japanese adults (n = 397). Personality traits were evaluated using the NEO Personality Inventory-Revised (NEO PI-R). A trend for lower Agreeableness in subjects born during winter (December to February) than other subjects was observed (P = 0.036, after correction for the multiple testing, multiple regression analysis adjusting for age and sex). Other major factors of the NEO PI-R, including Neuroticism, Extraversion, Openness and Conscientiousness, were not affected by season of birth. Further studies may be recommended to confirm the results, considering the relatively limited sample size. Evaluation of cognitive functions and behaviors using other measures including event-related potentials and functional MRI may also help the interpretation of the present result.

Adult↗
PubMed2005

Statistical and computational methods for comparative proteomic profiling using liquid chromatography-tandem mass spectrometry.

The combined method of LC-MS/MS is increasingly being used to explore differences in the proteomic composition of complex biological systems. The reliability and utility of such comparative protein expression profiling studies is critically dependent on an accurate and rigorous assessment of quantitative changes in the relative abundance of the myriad of proteins typically present in a biological sample such as blood or tissue. In this review, we provide an overview of key statistical and computational issues relevant to bottom-up shotgun global proteomic analysis, with an emphasis on methods that can be applied to improve the dependability of biological inferences drawn from large proteomic datasets. Focusing on a start-to-finish approach, we address the following topics: 1) low-level data processing steps, such as formation of a data matrix, filtering, and baseline subtraction to minimize noise, 2) mid-level processing steps, such as data normalization, alignment in time, peak detection, peak quantification, peak matching, and error models, to facilitate profile comparisons; and, 3) high-level processing steps such as sample classification and biomarker discovery, and related topics such as significance testing, multiple testing, and choice of feature space. We report on approaches that have recently been developed for these steps, discussing their merits and limitations, and propose areas deserving of further research.

Animals↗