Reliability of utricular function testing using a sinusoidal translation profile during unilateral centrifugation

The unilateral centrifugation test is one of the few vestibular tests that evaluate the utricles side by side. During this test, a subject is rotated about an earth vertical axis at high rotation speeds (e.g. 400 °/s) and translated sideways along the interaural axis to align the axis of rotation consecutively with the right and the left utricle. The combined rotation and translation induces ocular counter rolling (OCR), which is measured using three-dimensional video-oculography. Recently, a new model has been proposed to analyse the OCR. The model is based on contributions from both the semicircular canals and the utricles. Concomitant with the new model a new stimulation profile using a sinusoidal translation profile during the unilateral centrifugation has been introduced [1]. The current study presents the test-retest reliability as well as the robustness of the new stimulation method, based on data of 67 healthy subjects. Test-retest reliability was based on repeated measurements of a group of subjects. To test the robustness of the new sinusoidal translation paradigm, we investigated the effect of a different amplitude of the sinusoidal translation (6 cm instead of 4 cm) and of an offset in translation (from ?3 to +5 cm, instead of from ?4 to +4 cm) on the parameters. Several statistical measures were used to reflect the reliability: intraclass correlation coefficient (ICC), the “coefficient of variation of the method error” and the “minimal difference” (MD). All relevant variables from the physiological model for the OCR induced by unilateral centrifugation show a good to excellent reliability during the test-retest study and the relevant parameters remain unaffected by the changes applied to the translation profile (p > 0.05) as predicted by the model. Additionally, all observed differences are smaller than the MD values calculated in the test-retest part of the study.     

Preliminary mechanical characterization of the small bowel for in vivo robotic mobility

In this work we present test methods, devices, and preliminary results for the mechanical characterization of the small bowel for intra luminal robotic mobility. Both active and passive forces that affect mobility are investigated. Four investigative devices and testing methods to characterize the active and passive forces are presented in this work: (1) a novel manometer and a force sensor array that measure force per cm of axial length generated by the migrating motor complex, (2) a biaxial test apparatus and method for characterizing the biomechanical properties of the duodenum, jejunum, and ileum, (3) a novel in vitro device and protocol designed to measure the energy required to overcome the self-adhesivity of the mucosa, and (4) a novel tribometer that measures the in vivo coefficient of friction between the mucus membrane and the robot surface. The four devices are tested on a single porcine model to validate the approach and protocols. Mean force readings per cm of axial length of intestine that occurred over a 15?min interval in vivo were 1.34?±?0.14 and 1.18?±?0.22?N cm(-1) in the middle and distal regions, respectively. Based on the biaxial stress/stretch tests, the tissue behaves anisotropically with the circumferential direction being more compliant than the axial direction. The mean work per unit area for mucoseparation of the small bowel is 0.08?±?0.03 mJ cm(-2). The total energy to overcome mucoadhesion over the entire length of the porcine small bowel is approximately 0.55?J. The mean in vivo coefficient of friction (COF) of a curved 6.97 cm(2) polycarbonate sled on live mucosa traveling at 1?mm s(-1) is 0.016?±?0.002. This is slightly lower than the COF on excised tissue, given the same input parameters. We have initiated a comprehensive program and suite of test devices and protocols for mechanically characterizing the small bowel for in vivo mobility. Results show that each of the four protocols and associated test devices has successfully gathered preliminary data to confirm the validity of our test approach.     

Validation of physiological tests in relation to competitive performances in elite male distance cross-country skiing

The purpose of the present study was to establish which physiological test parameters reflects the distance performances in the Swedish National Championships in cross-country skiing (SNC) and the International Ski Federation's ranking points for distance performances (FISdist). The present study also aimed to create multiple regression models to describe skiing performance for the SNC distance races and International Ski Federation's (FIS) ranking. Twelve male, Swedish, national elite, cross-country skiers (maximal oxygen consumption [·VO?max] = 5.34 ± 0.34 L·min?1) volunteered to participate in the study. Their results in the 2008 SNC (15 km race [SNC15] and 30 km race [SNC30]) and FISdist points were used as performance data. On the week preceding the Championship, subjects completed a test battery consisting of 7 physiological tests: isokinetic knee extension peak torque (PT), vertical jumps (VJ), lactate threshold (LT), ·VO?max, and 3 double poling tests of different durations (DP20, DP60, and DP360). Correlations were established using Pearson's correlation analysis, and models to describe skiing performance were created using standard multiple linear regression analysis. Significant correlations were found between the performance parameters and test parameters derived from LT, ·VO?max, and DP60 tests. No correlations with any performance parameter were found for PT, VJ, DP20, and DP360 tests. For FISdist and SNC15, the models explain 81% and 78% of the variance in performance, respectively. No statistically valid regression model was found for SNC30. The results of this study imply that the physiological demands in male elite distance cross-country skiing performances are different in different events. To adequately evaluate a skier's performance ability in distance cross-country skiing, it is necessary to use test parameters and regression models that reflect the specific performance.     

Frequency responses of cat rapidly adapting mechanoreceptive fibers

The frequency responses of 11 rapidly adapting (RA) fibers in cat were studied by representing the average firing rate as a function of sinusoidal stimulus amplitude and stimulus frequency. Specifically, rate-intensity functions at different stimulation frequencies were fitted by four-parameter (a₀, a₁, a₂, a₃), piece-wise linear functions using nonlinear regression (n = 59; R² > 0.877). Rate-intensity functions at intermediate frequencies were found by linear interpolation. The result of this analysis is rate–amplitude–frequency functions plotted as two-dimensional surfaces. The surfaces consist of five regions separated and sufficiently defined by four space curves. At 14 different frequencies, the statistical distribution of each rate-intensity-function parameter could be approximated by a particular lognormal distribution (n = 56; R² > 0.796). The Kolmogorov–Smirnov test fails to reject this hypothesis for each combination of frequency and parameter (56 tests; p > 0.39). Therefore, at a given frequency, the variation of the parameters can be represented by lognormal distributions with specific means and standard deviations. Responses of six RA fibers, which are different from the data-set used for modeling, were compared with the stochastic model at different frequencies. The parameters of those fibers were tested against the null hypotheses that they were sampled from the particular parameter distributions dictated by the model. The Kolmogorov–Smirnov test fails to reject all the hypotheses at the α = 0.05 level (44 tests). At the α = 0.10 level, only a few test parameters were found to be departing from the model (a₀ and a₁ at 5?Hz; a₂ at 20?Hz; a₂ and a₃ at 50?Hz). The remaining test parameters could be accurately described by the model. Having confirmed the validity of the model, the logarithmic means and the logarithmic standard deviations of the lognormally distributed rate-intensity-function parameters were estimated in the frequency range of 4–200?Hz. The rate–amplitude–frequency surfaces sampled from the established stochastic model completely characterize the rate responses of RA fibers to sinusoidal stimuli and are superior to tuning curves which require selecting criterion responses. The current rate-response model is promising for future computational work, especially on population modeling.     

Powerful Haplotype-Based Hardy-Weinberg Equilibrium Tests for Tightly Linked Loci

Recently, there have been many case-control studies proposed to test for association between haplotypes and disease, which require the Hardy-Weinberg equilibrium (HWE) assumption of haplotype frequencies. As such, haplotype inference of unphased genotypes and development of haplotype-based HWE tests are crucial prior to fine mapping. The goodness-of-fit test is a frequently-used method to test for HWE for multiple tightly-linked loci. However, its degrees of freedom dramatically increase with the increase of the number of loci, which may lack the test power. Therefore, in this paper, to improve the test power for haplotype-based HWE, we first write out two likelihood functions of the observed data based on the Niu''s model (NM) and inbreeding model (IM), respectively, which can cause the departure from HWE. Then, we use two expectation-maximization algorithms and one expectation-conditional-maximization algorithm to estimate the model parameters under the HWE, IM and NM models, respectively. Finally, we propose the likelihood ratio tests LRT and LRT for haplotype-based HWE under the NM and IM models, respectively. We simulate the HWE, Niu''s, inbreeding and population stratification models to assess the validity and compare the performance of these two LRT tests. The simulation results show that both of the tests control the type I error rates well in testing for haplotype-based HWE. If the NM model is true, then LRT is more powerful. While, if the true model is the IM model, then LRT has better performance in power. Under the population stratification model, LRT is still more powerful. To this end, LRT is generally recommended. Application of the proposed methods to a rheumatoid arthritis data set further illustrates their utility for real data analysis.     

The Relative Power of Two Asymptotic Multivariate Tests for Homogeneity in a Contingency Table

In a three way contingency table two multivariate tests for homogeneity have been proposed by the author (1983) a the “catanova” test, which is a trace “metric” test and b the “multinova” test which is determinant based. Both tests are asymptotically distributed as chi-square. In this paper, the power values of the tests are compared and conditions are given for preference of each test.     

Frequency responses of cat rapidly adapting mechanoreceptive fibers

The frequency responses of 11 rapidly adapting (RA) fibers in cat were studied by representing the average firing rate as a function of sinusoidal stimulus amplitude and stimulus frequency. Specifically, rate-intensity functions at different stimulation frequencies were fitted by four-parameter (a0, a1, a2, a3), piece-wise linear functions using nonlinear regression (n = 59; R2 > 0.877). Rate-intensity functions at intermediate frequencies were found by linear interpolation. The result of this analysis is rate-amplitude-frequency functions plotted as two-dimensional surfaces. The surfaces consist of five regions separated and sufficiently defined by four space curves. At 14 different frequencies, the statistical distribution of each rate-intensity-function parameter could be approximated by a particular lognormal distribution (n = 56; R2 > 0.796). The Kolmogorov-Smirnov test fails to reject this hypothesis for each combination of frequency and parameter (56 tests; p > 0.39). Therefore, at a given frequency, the variation of the parameters can be represented by lognormal distributions with specific means and standard deviations. Responses of six RA fibers, which are different from the data-set used for modeling, were compared with the stochastic model at different frequencies. The parameters of those fibers were tested against the null hypotheses that they were sampled from the particular parameter distributions dictated by the model. The Kolmogorov-Smirnov test fails to reject all the hypotheses at the alpha = 0.05 level (44 tests). At the alpha = 0.10 level, only a few test parameters were found to be departing from the model (a0 and a1 at 5 Hz; a2 at 20 Hz; a2 and a3 at 50 Hz). The remaining test parameters could be accurately described by the model. Having confirmed the validity of the model, the logarithmic means and the logarithmic standard deviations of the lognormally distributed rate-intensity-function parameters were estimated in the frequency range of 4-200 Hz. The rate-amplitude-frequency surfaces sampled from the established stochastic model completely characterize the rate responses of RA fibers to sinusoidal stimuli and are superior to tuning curves which require selecting criterion responses. The current rate-response model is promising for future computational work, especially on population modeling.     

Rodent models for mania: practical approaches

The scarcity of good animal models for bipolar disorder (BPD) and especially for mania is repeatedly mentioned as one of the rate-limiting factors in the process of gaining a better understanding into its pathophysiology and of developing better treatments. Standard models of BPD have some value but usually represent only one facet of the disease and have partial validity. A number of new approaches for modeling BPD and specifically mania have been suggested in the last few years and can be combined to improve models. These approaches include targeted mutation models representing reverse translation, the identification of advantageous strains for components of the disorder, a search for the most homologous species to address specific human pathology, and the exploration of individual differences of response including the separation between susceptible and resilient animals. Additionally, recent efforts have identified and developed new tests to distinguish between “normal” and “BPD-like” animals including the different utilization of known tests and novel tests such as the female-urine-sniffing test and behavior pattern monitor analysis. Additional tests relating to further domains of BPD are still needed. An ideal model for BPD that will encompass the entire disease and be useful for every demand will probably not become available until we have a full understanding of the pathophysiology of the disorder. However, the current advances in modeling should lead to better comprehension of the disorder and therefore to the gradual development of increasingly improved models.     

Effect of circadian rhythm type on serum lipid levels in shift workers: A 5-year cohort study

We investigated how differences in circadian rhythm type affect the health of workers engaged in shift work. Employees, who were newly hired in a steel company between 2007 and 2011, received the Morningness–Eveningness Questionnaire (MEQ) survey. The target participants were 153 male shift workers who were not being treated with any antihyperlipidemic drugs and underwent periodic physical examinations including blood tests at least twice. According to the score of the MEQ at the time of joining the company, we classified the subjects into five types. Longitudinal changes in serum lipid level were estimated among the circadian rhythm types adjusted for age, BMI, and other covariates using a linear mixed model. The regression coefficient of total cholesterol level in the “definitely and moderately morning” group was ?17.83 (95% confidence interval (CI): ?33.42 to ?2.23), and in the “intermediate ‘group’ was ?16.84 [95% CI: ?30.40 to ?3.28], compared to the moderate evening type.” The total cholesterol level was higher in the moderately evening type than in any of the other groups. Between the Morningness–Eveningness (ME) type and Low-density lipoprotein (LDL) cholesterol levels, compared with the “moderately evening type” group, the regression coefficient in the “intermediate type” group was ?16.08 (95% CI: ?28.79 to ?3.37), and in the “definitely and moderately morning type” group was ?17.50 [95% CI: ?32.11 to ?2.88]. The “moderately evening type” group had a higher LDL cholesterol level than any of the other groups. Evening-type circadian rhythm type shift workers are more prone to elevated serum lipid levels.     

Survivor Curves for Leptospira autumnalis Akiyami A Based on Most-Probable-Number Values

The validity of survivor curves for Leptospira autumnalis Akiyami A based on most-probable-number values is supported by the following observations: (i) linear regression lines fell within most of the 95% confidence intervals; (ii) linear correlation coefficients (r) were consistently high (i.e., near -1); and (iii) statistical tests for goodness of fit usually accepted the linear model. These tests are consistent with an exponential death rate for the test organism in defined solutions. The influence of temperature and pH on survival was demonstrated by showing a statistically significant difference in survivor curve slopes.     

A linearized and incompressible constitutive model for arteries

In many biomechanical studies, blood vessels can be modeled as pseudoelastic orthotropic materials that are incompressible (volume-preserving) under physiological loading. To use a minimum number of elastic constants to describe the constitutive behavior of arteries, we adopt a generalized Hooke's law for the co-rotational Cauchy stress and a recently proposed logarithmic-exponential strain. This strain tensor absorbs the material nonlinearity and its trace is zero for volume-preserving deformations. Thus, the relationships between model parameters due to the incompressibility constraint are easy to analyze and interpret. In particular, the number of independent elastic constants reduces from ten to seven in the orthotropic model. As an illustratory study, we fit this model to measured data of porcine coronary arteries in inflation-stretch tests. Four parameters, n (material nonlinearity), Young's moduli E? (circumferential), E? (axial), and E? (radial) are necessary to fit the data. The advantages and limitations of this model are discussed.     

THE BETA-BINOMIAL MODEL: ACCOUNTING FOR INTER-TRIAL VARIATION IN REPLICATED DIFFERENCE AND PREFERENCE TESTS

Binomial tests are commonly used in sensory difference and preference testing under the assumptions that choices are independent and choice probabilities do not vary from trial to trial. This paper addresses violations of the latter assumption (often referred to as overdispersion) and accounts for variation in inter-trial choice probabilities following the Beta distribution. Such variation could arise as a result of differences in test substrate from trial to trial, differences in sensory acuity among subjects or the existence of latent preference segments. In fact, it is likely that overdispersion occurs ubiquitously in product testing. Using the Binomial model for data in which there is inter-trial variation may lead to seriously misleading conclusions from a sensory difference or preference test. A simulation study in this paper based on product testing experience showed that when using a Binomial model for overdispersed Binomial data, Type I error may be 0.44 for a Binomial test specification corresponding to a level of 0.05. Underestimation of Type I error using the Binomial model may seriously undermine legal claims of product superiority in situations where overdispersion occurs. The Beta-Binomial (BB) model, an extension of the Binomial distribution, was developed to fit overdispersed Binomial data. Procedures for estimating and testing the parameters as well as testing for goodness of fit are discussed. Procedures for determining sample size and for calculating estimate precision and test power based on the BB model are given. Numerical examples and simulation results are also given in the paper. The BB model should improve the validity of sensory difference and preference testing.     

Elimination of inbreeding depression from a captive population of Speke's gazelle: Validity of the original statistical analysis and confirmation by permutation testing

The Speke's gazelle captive breeding program was designed in the early 1980s to simultaneously maintain the population's genetic diversity while reducing the severity of the inbreeding depression in a situation in which inbreeding could not be avoided. Statistical analyses of the resulting data using both regression techniques and nonparametric exact contingency tests revealed that the inbreeding depression was indeed reduced, and genetic surveys revealed that high levels of nuclear genetic diversity had indeed been maintained. Hence, the twin goals of the breeding program appeared to have been achieved. Recently, several papers have been published that question the validity of the original statistical analyses and resulting biological conclusions. Specifically, these papers raise three major issues: (1) that a small sample correction factor used in the regression analysis represents a statistical “flaw,” (2) that new analyses of the data do not confirm the original conclusion of a significant reduction in the level of inbreeding depression, and (3) that the biological conclusions about the program are not justified. In this paper we show (1) that there is no “flaw” in the small sample correction, (2) that the recent permutational test given by Willis and Wiese seriously violates standard procedures and has no statistical validity, (3) that the regression procedures used by Ballou are inappropriate because the data seriously violate the underlying statistical assumptions and that the statistically valid components of Ballou's work strongly confirm the validity of the Speke's gazelle program, (4) that permutational tests done in accordance with standard statistical practice strongly confirm the results of the original analysis, and (5) that the original biological conclusions are fully justified by multiple types of statistical analyses. Zoo Biol 17:77–94, 1998. © 1998 Wiley-Liss, Inc.     

Rodent Gymnastics: Neurobehavioral Assays in Ischemic Stroke

Despite years of research, most preclinical trials on ischemic stroke have remained unsuccessful owing to poor methodological and statistical standards leading to “translational roadblocks.” Various behavioral tests have been established to evaluate traits such as sensorimotor function, cognitive and social interactions, and anxiety-like and depression-like behavior. A test’s validity is of cardinal importance as it influences the chance of a successful translation of preclinical results to clinical settings. The mission of choosing a behavioral test for a particular project is, therefore, imperative and the present review aims to provide a structured way to evaluate rodent behavioral tests with implications in ischemic stroke.     

Does IQ Really Predict Job Performance?

IQ has played a prominent part in developmental and adult psychology for decades. In the absence of a clear theoretical model of internal cognitive functions, however, construct validity for IQ tests has always been difficult to establish. Test validity, therefore, has always been indirect, by correlating individual differences in test scores with what are assumed to be other criteria of intelligence. Job performance has, for several reasons, been one such criterion. Correlations of around 0.5 have been regularly cited as evidence of test validity, and as justification for the use of the tests in developmental studies, in educational and occupational selection and in research programs on sources of individual differences. Here, those correlations are examined together with the quality of the original data and the many corrections needed to arrive at them. It is concluded that considerable caution needs to be exercised in citing such correlations for test validation purposes.     

Partitioning to uncover conditions for permutation tests to control multiple testing error rates

This article discusses specific assumptions necessary for permutation multiple tests to control the Familywise Error Rate (FWER). At issue is that, in comparing parameters of the marginal distributions of two sets of multivariate observations, validity of permutation testing is affected by all the parameters in the joint distributions of the observations. We show the surprising fact that, in the case of a linear model with i.i.d. errors such as in the analysis of Quantitative Trait Loci (QTL), this issue has no impact on control of FWER, if the test statistic is of a particular form. On the other hand, in the analysis of gene expression levels or multiple safety endpoints, unless some assumption connecting the marginal distributions of the observations to their joint distributions is made, permutation multiple tests may not control FWER.     

Does low back pain affect the reliability of postural regulation?

The aim of this study was to examine the intraobserver reliability of a posturographic assessment in patients with low back pain. We investigated 24 symptomatic subjects with defined low back pain (mean: 57.9?years) and a pair-matched control group including 24 asymptomatic persons (mean: 58.1?years). Each participant underwent two measurements on a posturographic device (32?Hz sampling rate) based on the Interactive Balance System (time interval: 7?d). Test procedure consisted of tests on solid ground with eyes open (1) and eyes closed (2). Data analysis included parameters of motor output and a frequency band analysis. Reliability tests were realized using by intraclass correlations (ICC). Coefficients of ICC ranged from 0.36 (95% CI: 0.01–0.73) to 0.94 (95% CI: 0.86–0.97) in both test positions. For 69% (11/16) of the investigated parameters a high level (ICC?>?0.75) of intraobserver reliability was reached. Based on the results, the posturographic measurement system used in this study seems to be appropriate for use in longitudinal study designs in an orthopaedic setting.     

Conjugate and Other Distributional Methods in Configural Frequency Analysis

Configural Frequency Analysis (CFA) is being increasingly used by psychologists and other researchers to test for the presence of combinations of categorical variables which occur more frequently or less frequently than expected under a particular model of chance. Configurations which occur more frequently than chance are known as “Types”-Configurations which are conspicuous by their absence or rarity are known as “Antitypes”. Most configural frequency test theory consists of binomial tests applied to the cells of a cross-tabulation table. The wide variety of statistical tests described in papers and books on CFA are approximations to the binomial test, due to the computational intensity associated with performing binomial tests directly (VON EYE, 1990b). This paper advocates direct computation of binomial probabilities instead of the usual approximations used in CFA. Mathematical relationships of the binomial distribution with the F and incomplete beta distributions are described which enable the researcher to efficiently compute binomial probabilities using functions available in common statistical software. The classical inference approach adopted by traditional CFA makes it difficult to make conclusions regarding the likely prevalence rates of types or antitypes in the reference population. It is also not possible to exploit additional information about the sample which, while not known precisely, is known with a degree of confidence and can aid in the identification of types and antitypes. A Bayesian conjugate distributions approach based on the incomplete beta distribution is proposed. Bayesian extensions of this model to both classical CFA and a sequential CFA analysis advanced by KIESER and VICTOR (1991) are described.     

Tests of two methods for identifying founder effects in metapopulations reveal substantial type II error

Genetic analysis has been promoted as a way to reconstruct recent historical dynamics (“historical demography”) by screening for signatures of events, such as bottlenecks, that disrupt equilibrium patterns of variation. Such analyses might also identify “metapopulation” processes like extinction and recolonization or source-sink dynamics, but this potential remains largely unrealized. Here we use simulations to test the ability of two currently used strategies to distinguish between a set of interconnected subpopulations (demes) that have undergone bottlenecks or extinction and recolonization events (metapopulation dynamics) from a set of static demes. The first strategy, decomposed pairwise regression, provides a holistic test for heterogeneity among demes in their patterns of isolation-by-distance. This method suffered from a type II error rate of 59–100 %, depending on parameter conditions. The second strategy tests for deviations from mutation-drift equilibrium on a deme-by-deme basis to identify sites likely to have experienced recent bottlenecks or founder effects. Although bottleneck tests have good statistical power for single populations with recent population declines, their validity in structured populations has been called into question, and they have not been tested in a metapopulation context with immigration (or colonization) and population recovery. Our simulations of hypothetical metapopulations show that population recovery can rapidly eliminate the statistical signature of a bottleneck, and that moderate levels of gene flow can generate a false signal of recent population growth for demes in equilibrium. Although we did not cover all possible metapopulation scenarios, the performance of the tests was disappointing. Our results indicate that these methods might often fail to identify population bottlenecks and founder effects if population recovery and/or gene flow are influential demographic features of the study system.