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Clinical auditory brain stem response latency measures are conventionally evaluated for abnormality by reference to normative laboratory values in standard deviation units. This note suggests that the directionality of the test hypothesis should be considered when the clinical ABR is evaluated for abnormality at a predetermined level of confidence.
Human patient simulators are widely used to train health professionals and students in a clinical setting, but they also can be used to enhance physiology education in a laboratory setting. Our course incorporates the human patient simulator for experiential learning in which undergraduate university juniors and seniors are instructed to design, conduct, and present (orally and in written form) their project testing physiological adaptation to an extreme environment. This article is a student report on the physiological response to acute carbon monoxide exposure in a simulated healthy adult male and a coal miner and represents how 1) human patient simulators can be used in a nonclinical way for experiential hypothesis testing; 2) students can transition from traditional textbook learning to practical application of their knowledge; and 3) student-initiated group investigation drives critical thought. While the course instructors remain available for consultation throughout the project, the relatively unstructured framework of the assignment drives the students to create an experiment independently, troubleshoot problems, and interpret the results. The only stipulation of the project is that the students must generate an experiment that is physiologically realistic and that requires them to search out and incorporate appropriate data from primary scientific literature. In this context, the human patient simulator is a viable educational tool for teaching integrative physiology in a laboratory environment by bridging textual information with experiential investigation.
Four replicate experiments were performed to test the hypothesis that a 4-hr exposure of L929 cells in vitro to a 60 Hz, 10 microT magnetic field results in a large increase in ornithine decarboxylase (ODC) enzyme activity (1-2). A positive control yielded a highly statistically significant increase in ODC activity. However, magnetic field exposure had no statistically significant effect on extractable ODC activity of L929 cells relative to that of sham-exposed cells.
Rigorous experimental design can minimize the high risk of false positives and false negatives in the behavioral phenotyping of a new transgenic or knockout mouse. Use of well established, quantitative, reproducible behavioral tasks, appropriate Ns, correct statistical methods, consideration of background genes contributed by the parental strains, and attention to litter and gender issues, will maximize meaningful comparisons of -/-, +/-, and +/+ genotypes. Strategies developed and used by our laboratory are described in this review. Preliminary observations evaluate general health and neurological reflexes. Sensory abilities and motor functions are extensively quantitated. Specific tests include observations of home cage behaviors, body weight, body temperature, appearance of the fur and whiskers, righting reflex, acoustic startle, eye blink, pupil constriction, vibrissae reflex, pinna reflex, Digiscan open field locomotion, rotarod motor coordination, hanging wire, footprint pathway, visual cliff, auditory threshold, pain threshold, and olfactory acuity. Hypothesis testing then focuses on at least three well-validated tasks within each relevant behavioral domain. Specific tests for mice are described herein for the domains of learning and memory, feeding, nociception, and behaviors relevant to discrete symptoms of human anxiety, depression, schizophrenia, and drug addiction. An example of our approach is illustrated in the behavioral phenotyping of C/EBPdelta knockout mice, which appear to be normal on general health, neurological reflexes, sensory and motor tasks, and the Morris water task, but show remarkably enhanced performance on contextual fear conditioning.
This study conducted an approximate replication of the Lindeman and Van Aernam study (1971) on a sample of 49 patients from a large metropolitan hospital. Factors controlled in this study that were not present in the original study included sample restrictions to patients of three surgeons with similar techniques and to patients having lower or upper abdominal surgery. Structured pre-operative teaching was conducted primarily by the principle investigator and associate and a check list was used to indicate that the patients could perform the deep breathing, coughing, and exercises. For this sample, using p = .05, structured pre-operative instruction improved significantly the ability of the patients to deep breathe and cough post-operatively as measured by pulmonary function tests. Hypothesis I was supported. Structured pre-operative instruction did not reduce significantly the mean length of hospital stay and hypothesis II was not supported.
The regressive models describe familial patterns of dependence of quantitative measures by specifying regression relationships among a person's phenotype and genotype and the phenotypes and genotypes of antecedents. When the number of sibs in the pattern of dependence increases, as in the class D regressive model, computation of the likelihood becomes time consuming, since the Elston-Stewart algorithm cannot be used generally. On the other hand, the simpler class A regressive model, which imposes a restriction on the sib-sib correlation, may lead to inference of a spurious major gene, as already observed in some instances. A simulation study is performed to explore the robustness of class A model with respect to false inference of a major gene and to search for faster methods of computing the likelihood under class D model. The class A model is not robust against the presence of a sib-sib correlation exceeding that specified by the model, unless tests on transmission probabilities are performed carefully: false detection of a major gene is reduced from a number of 26-30 to between 0 and 4 data sets out of 30 replicates after testing both the Mendelian transmission and the absence of transmission of a major effect against the general transmission model. Among various approximations of the likelihood formulation of the class D model, approximations 6 and 8 are found to work appropriately in terms of both the estimation of all parameters and hypothesis testing, for each generating model. These approximations lessen the computer time by allowing use of the Elston-Stewart algorithm.
A consecutive series of 110 undertermined deaths (U.D.) was compared with matched samples of suicides and accidents recorded in the same metropolitan Coroner's District. The hypothesis tested was that U.D. are mostly concealed suicides and will resemble known suicides more closely than accidents. The samples were compared on social and demographic variables, psychiatric and physical illness, evidence of suicide intent, information available to the Coroner and the circumstances of death. The results did not confirm the hypothesis. The study widens the investigation of the mortality of mental disorder from unnatural causes beyond the category of suicide.
In this paper, we address the problem of calculating power and sample sizes associated with simultaneous tests for non-inferiority. We consider the case of comparing several experimental treatments with an active control. The approach is based on the ratio view, where the common non-inferiority margin is chosen to be some percentage of the mean of the control treatment. Two power definitions in multiple hypothesis testing, namely, complete power and minimal power, are used in the computations. The sample sizes associated with the ratio-based inference are also compared with that of a comparable inference based on the difference of means for various scenarios. It is found that the sample size required for ratio-based inferences is smaller than that of difference-based inferences when the relative non-inferiority margin is less than one and when large response values indicate better treatment effects. The results are illustrated with examples.
The general (g) factor is the most general and relevant cognitive ability. This factor is considered to be one of the most important predictors of academic achievement and of many other socially relevant behavioral outcomes. In the last decades, many researchers have investigated the possible changes in the relevance of the g factor from childhood to adulthood. The indifferentiation hypothesis states that the variance attributed to the g factor and the main cognitive abilities will not change over the life span. In the present study, the authors tested that hypothesis in childhood, adolescence, and adulthood by using 2 different cognitive batteries (Test of Educational Ability [TEA; S. A. TEA, 1999], Wechsler Adult Intelligence Scales [WAIS; D. Wechsler, 1955]), which they administered in 2 different countries--Spain (TEA) and the United States (WAIS). The ages of the participants (N = 2,384) ranged from 8 to 54 years. Results showed that the number of factors extracted and the relevance were the same for every age group in both batteries, as predicted by the indifferentiation hypothesis. The authors discuss implications of intelligence assessment.
In this work parametric and non-parametric statistical methods are proposed to analyze Diffusion Tensor Magnetic Resonance Imaging (DT-MRI) data. A Multivariate Normal Distribution is proposed as a parametric statistical model of diffusion tensor data when magnitude MR images contain no artifacts other than Johnson noise. We test this model using Monte Carlo (MC) simulations of DT-MRI experiments. The non-parametric approach proposed here is an implementation of bootstrap methodology that we call the DT-MRI bootstrap. It is used to estimate an empirical probability distribution of experimental DT-MRI data, and to perform hypothesis tests on them. The DT-MRI bootstrap is also used to obtain various statistics of DT-MRI parameters within a single voxel, and within a region of interest (ROI); we also use the bootstrap to study the intrinsic variability of these parameters in the ROI, independent of background noise. We evaluate the DT-MRI bootstrap using MC simulations and apply it to DT-MRI data acquired on human brain in vivo, and on a phantom with uniform diffusion properties.
Health-Related Quality of Life (HRQoL) measures are becoming increasingly used in clinical trials as primary outcome measures. Investigators are now asking statisticians for advice on how to analyse studies that have used HRQoL outcomes.HRQoL outcomes, like the SF-36, are usually measured on an ordinal scale. However, most investigators assume that there exists an underlying continuous latent variable that measures HRQoL, and that the actual measured outcomes (the ordered categories), reflect contiguous intervals along this continuum. The ordinal scaling of HRQoL measures means they tend to generate data that have discrete, bounded and skewed distributions. Thus, standard methods of analysis such as the t-test and linear regression that assume Normality and constant variance may not be appropriate. For this reason, conventional statistical advice would suggest that non-parametric methods be used to analyse HRQoL data. The bootstrap is one such computer intensive non-parametric method for analysing data. We used the bootstrap for hypothesis testing and the estimation of standard errors and confidence intervals for parameters, in four datasets (which illustrate the different aspects of study design). We then compared and contrasted the bootstrap with standard methods of analysing HRQoL outcomes. The standard methods included t-tests, linear regression, summary measures and General Linear Models.Overall, in the datasets we studied, using the SF-36 outcome, bootstrap methods produce results similar to conventional statistical methods. This is likely because the t-test and linear regression are robust to the violations of assumptions that HRQoL data are likely to cause (i.e. non-Normality). While particular to our datasets, these findings are likely to generalise to other HRQoL outcomes, which have discrete, bounded and skewed distributions. Future research with other HRQoL outcome measures, interventions and populations, is required to confirm this conclusion.
BACKGROUND: In cell culture experiments, flupirtine maleate (FLU), a triaminopyridine compound, was able to protect neuronal cells from apoptotic cell death induced by prion protein fragments and beta-amyloid peptides. As FLU is a clinically safe drug, the authors started a double-blind placebo-controlled study in patients with Creutzfeldt-Jakob disease (CJD). METHODS: Twenty-eight patients with CJD were randomized to an oral treatment with either FLU (n = 13) or matching placebo (PLA; n = 15). For inclusion and continuing the study, the patients had to achieve at least 50% in two of the subscales of the dementia tests employed. A battery of standardized questionnaires was employed to monitor the progression of the disease. The main outcome variable was the cognitive part of the Alzheimer's Disease Assessment Scale (ADAS-Cog); the difference between baseline and the best score under treatment was defined as the primary efficacy variable for hypothesis testing. RESULTS: CJD types were homogeneously distributed among the treatment groups. Patients treated with FLU showed significantly less deterioration in the dementia tests than patients treated with PLA. The mean change in ADAS-Cog (baseline to best) was +8.4 (+/-15.3) in the FLU group and +20.6 (+/-15.1) in the PLA group (p = 0.02, one-sided t-test). CONCLUSIONS: FLU has beneficial effects on cognitive function in patients with CJD. These positive results also may suggest a treatment potential of FLU in other neurodegenerative disorders. However, further studies are necessary.
This study was designed to examine the relationship of hand preference to performance on a thumb-positioning task. Two hypotheses were proposed on the basis of hemispheric lateralization. The first stated that all subjects would perform the task more accurately using the left thumb, regardless of hand preference. The second hypothesis tested was that left-handed subjects would perform more accurately than right-handed subjects. Each of 20 neurologically intact adults grouped by hand preference reproduced a criterion thumb position with both thumbs simultaneously. Absolute error, recorded for each movement and analyzed by mixed analysis of variance, did support the first hypothesis. However, the left-handed group did not perform statistically differently from right-handed subjects. Factors influencing the data are discussed and recommendations for further studies are made.
Public health researchers are sometimes required to make adjustments for multiple testing in reporting their results, which reduces the apparent significance of effects and thus reduces statistical power. The Bonferroni procedure is the most widely recommended way of doing this, but another procedure, that of Holm, is uniformly better. Researchers may have neglected Holm's procedure because it has been framed in terms of hypothesis test rejection rather than in terms of P values. An adjustment to P values based on Holm's method is presented in order to promote the method's use in public health research.
Advocates of maximum likelihood (ML) approaches to phylogenetics commonly cite as one of their primary advantages the use of objective statistical criteria for model selection. Currently, a particular implementation of the likelihood ratio test (LRT) is the most commonly used model-selection criterion in phylogenetics. This approach requires the choice of a starting point and a parameter addition (or removal) sequence that can affect all ML inferences (i.e., topology, model, and all evolutionary parameters). Here, several alternative starting points and parameter sequences are tested in empirical data sets to assess their influence on model selection and optimal topology. In the studied data sets, varying model-selection protocols leads to selection of different models that, in some cases, lead to different ML trees. Given the sensitivity of the LRT, some possible solutions to model selection (within the hypothesis testing approach) are outlined, and alternative model-selection criteria are discussed. Some of the suggested alternatives seem to lack these problems, although their behavior and adequacy for phylogenetics needs to be further explored.
The Department of Veterans Affairs identifies 195,000 servicemen as being involved in the occupation of Hiroshima and Nagasaki, with an additional 210,000 personnel participating in 200 post-war nuclear tests. In 1995, the Institute of Medicine declined to recommend a study of the reproductive outcomes of Atomic Veterans. This article revisits the Institute of Medicine decision. Health effects and legislation provide the framework for a critical analysis of the Japanese data as it applies to Atomic Veterans. It explores the role of traditional hypothesis testing in legislative decisions and offers an in-depth exploration of paternal contributions to adverse reproductive events. It emphasizes the risks faced by reproductive age males when exposed to environmental hazards such as ionizing radiation.
A market orientation culture has been described as one that blends an organization's commitment to customer value with a process of continuously creating superior value for customers. Developing such a culture is further described as (1) obtaining information about customers, competitors, and markets, (2) examining the gathered information from a total organizational perspective, (3) deciding how to deliver superior customer value, and (4) implementing actions to provide value to customers. A market orientation culture focuses on the customer, identifies issues in the competitive environment, and coordinates all functional areas to achieve organizational objectives. Research has found businesses with higher market orientation are more successful in achieving organizational objectives. The measurement of market orientation within businesses has been empirically tested and validated. However, empirical research on market orientation in nonprofit organizations such as universities has not been examined. This study investigated market orientation within the university setting, specifically Schools of Business Administration, and compared these data with previously published data within the business sector. Data for comparative purposes were collected via a national survey. Hypothesis testing was conducted. Results indicated significantly lower market orientation culture within the schools of business as reported by AACSB Business School Deans vis-à-vis managers of business enterprises.
As the preceding chapters illustrate, now that whole-genome scan analyses are becoming more common, there is considerable disagreement about the best way to balance between false positives and false negatives (traditionally called type I and type II errors in the statistical parlance). Type I and type II errors can be simultaneously controlled, if we are willing to let the sample size of analysis vary. This is the secret that Wald (1947) discovered in the 1940s that led to the theory of sequential sampling and was the inspiration for Newton Morton in developing the lod score method. We can exploit this idea further and capitalize on an old, but nearly forgotten theory: sequential multiple decision procedures (SMDP) (Bechhoffer, et al., 1968), which generalizes the standard "two-hypotheses" tests to consider multiple alternative hypotheses. Using this theory, we can develop a single, genome-wide test that simultaneously partitions all markers into "signal" and "noise" groups, with tight control over both type I and type II errors (Province, 2000). Conceiving this approach as an analysis tool for fixed sample designs (instead of a true sequential sampling scheme), we can let the data decide at which point we should move from the hypothesis generation phase of a genome scan (where multiple comparisons make the interpretation of p values and significance levels difficult and controversial), to a true hypothesis-testing phase (where the problem of multiple comparisons has been all but eliminated so that p values may be accepted at face value).