Unequal Variability Research Articles

An Evaluation of the Intubrite Laryngoscope in Simulated In-Hospital and Out-of-Hospital Settings by Individuals with No Clinical Experience: A Randomized, Cross-Over, Manikin Study.

Introduction: The aim of the study was to compare the Intubrite laryngoscope and the standard Macintosh blade laryngoscope (MCL) used by persons with no clinical experience in simulated hospital and non-hospital conditions on a manikin model. Materials and methods: The study involved 50 students of Medical Rescue. The hospital conditions (intubation height 110 cm—high position) and those occurring at the scene (intubation of a manikin located at floor level-low position) were simulated. The analysis included: duration of intubation, visibility of the laryngeal opening by the Cormack–Lehane scale, the bioelectrical activity of the intubating muscles, comfort and subjective assessment of physical effort by the Borg scale (Borg’s scale of subjective feeling of effort). The statistical analysis was performed with Microsoft Excel and T-student tests for pairs with unequal variables. The statistical importance was set at p < 0.05. Results: The use of an Intubrite laryngoscope significantly reduces the mean endotracheal intubation time compared to the Macintosh laryngoscope in a low position (17.34 s versus 19.04 s, p < 0.05). A higher rate of repeat intubations was observed in a low position for MCL (from 10% to 14%, p < 0.05). The reverse is true for Intubrite laryngoscope intubation (from 8% to 4%, p < 0.05 Please explain what is compared). The Intubrite laryngoscope improved visualization of glottis in the high and the low positions compared to the Macintosh laryngoscope (54% and 50% to 52% and 38%, respectively, p < 0.05). The risk of tooth damage was the same for the Intubrite and the MCL laryngoscopes in a high position (16% and 14%, respectively, p > 0.05), while in the simulated out-of-hospital setting, it was significantly higher for the MCL (22% versus 8%, p < 0.05). The subjective comfort of intubation in both simulated situations was similar according to the Borg scale (p-value, values). The use of the Intubrite laryngoscope was associated with less effort than the MCL in high versus low positions. For MCL, intubation in a high position was associated with lower mean muscle activity than in a low position (+48.24 µV versus +58.25 µV, p-value). For the Intubrite laryngoscope, these values were at similar levels (+52.03 µV and +52.65 µV, p-value). Conclusions: The use of the Intubrite laryngoscope by people with no clinical experience shortens the time of intubation and improves the laryngeal view compared to the standard Macintosh laryngoscope, but it requires similar muscle work in simulated conditions.

FISHERY OF OTOLITHOIDES PAMA (HAMILTON, 1822) IN NARMADA ESTUARY

Total estuarine area under Gujarat state is reported to be 0.21 lakh ha. Narmada estuary is a freshwater estuary under the tidal effect, which mainly influences the salinity regimes. The actual estuarine region starts from Bharuch (situated 220 25' 78 N, 730 53' 91 E) and joins Arabian Sea at Ambetha (210 40'81 N, 720 35' 70 E) in Bharuch district, Gujarat. The funnel-shaped 72 km-long estuarine occupies an area of 6,346 km2 (Kumar et al., 2014). The southwest monsoon brings rainfall, and about 70% of the rainfall occurs during the period from June to September. The development of sand bars at the mouth of the estuary reduces the tidal ingress into the system. Narmada estuary is influenced by semi-diurnal tides with unequal variability. The estuarine production reduced drastically from 15889 t (2006-2007) to 1618 t (2014-15). Habitat shifting of species due to salinity industrial effluents and formation of sand bar in the mouth of the estuary indicates restricted fish migration may be the cause

Bootstrapping Two-step Least Squares Approach for Solving Heteroscedasticity Problem in Linear Regression Analysis

In this study, the problem of heteroscedasticity which is referred to as unequal variability in linear regression analysis is considered. Bootstrapping Two Step Least Squares (BWLS) for controlling heteroscedasticity in linear regression analysis was proposed. This method was compared with other existing methods (Ordinary Least Squares, Weighted Least Squares, Two Step Least Squares, Bootstrap Weighted Least) based on the Root Mean Square Error (RMSE) of the regression coefficient and the Euclidean norm was used to measure the accuracy across all coefficients. Simulated data was used in the comparison. The results show that the proposed bootstrap method performed better than the other methods in performing regression analysis in the presence of heteroscedasticity across all the sample sizes and at various levels of heteroscedasticity considered from the analysis. Real life data was used to demonstrate the results, which corresponds with result obtain from the simulation studies.

An integrative shrinkage estimator for random-effects meta-analysis of rare binary events

Meta-analysis has been a powerful tool for inferring the treatment effect between two experimental conditions from multiple studies of rare binary events. Recently, under a random-effects (RE) model, Bhaumik et al. developed a simple average (SA) estimator and showed that with the continuity correction factor 0.5, the SA estimator was the least biased among a set of commonly used estimators. In this paper, under various RE models that allow for treatment groups with equal and unequal variability (in either direction), we develop an integrative shrinkage (iSHRI) estimator based on the SA estimator, which aims to improve estimation efficiency in terms of mean squared error (MSE) that accounts for the bias-variance tradeoff. Through simulation, we find that iSHRI has better performance in general when compared with existing methods, in terms of bias, MSE, type I error and confidence interval coverage. Data examples of rosiglitazone meta-analysis are provided as well, where iSHRI yields competitive results.

Meta-analysis of rare binary events in treatment groups with unequal variability.

Meta-analysis has been widely used to synthesize information from related studies to achieve reliable findings. However, in studies of rare events, the event counts are often low or even zero, and so standard meta-analysis methods such as fixed-effect models with continuity correction may cause substantial bias in estimation. Recently, Bhaumik etal. developed a simple average estimator for the overall treatment effect based on a random effects model. They proved that the simple average method with the continuity correction factor 0.5 (SA_0.5) is the least biased for large samples and showed via simulation that it has superior performance when compared with other commonly used estimators. However, the random effects models used in previous work are restrictive because they all assume that the variability in the treatment group is equal to or always greater than that in the control group. Under a general framework that explicitly allows treatment groups with unequal variability but assumes no direction, we prove that SA_0.5 is still the least biased for large samples. Meanwhile, to account for a trade-off between the bias and variance in estimation, we consider the mean squared error to assess estimation efficiency and show that SA_0.5 fails to minimize the mean squared error. Under a new random effects model that accommodates groups with unequal variability, we thoroughly compare the performance of various methods for both large and small samples via simulation and draw conclusions about when to use which method in terms of bias, mean squared error, type I error, and confidence interval coverage. A data example of rosiglitazone meta-analysis is used to provide further comparison.

Short-Run Control Chart for Multiproducts with Multi-Items Based on Unequal Means and Variances

Statistical process control (SPC) is one of the most important statistical tools for monitoring production processes. It can be effectively designed and implemented when the process or product specifications are consecutively observed from a mass production condition. Normally, short-cycle productions do not have sufficient data to implement SPC. This research introduced how to design and implement short-run control chart for batch production conditions. Monitoring critical specifications of supplied parts to automotive industry was proposed. The results revealed that unequal variables followed normal distribution and can be fluctuated over time for the purpose of monitoring multiple products for each product including multidimensions with unequal means and variances from the central line to control the chart. Out-of-control signals and nonrandom patterns can be recognized on the developed short-run control chart accordingly.

Using response time modeling to distinguish memory and decision processes in recognition and source tasks.

Receiver operating characteristic (ROC) functions are often used to make inferences about memory processes, such as claiming that memory strength is more variable for studied versus nonstudied items. However, decision processes can produce the ROC patterns that are usually attributed to memory, so independent forms of data are needed to support strong conclusions. The present experiments tested ROC-based claims about the variability of memory evidence by modeling response time (RT) data with the diffusion model. To ensure that the model can correctly discriminate equal- and unequal-variance distributions, Experiment 1 used a numerousity discrimination task that had a direct manipulation of evidence variability. Fits of the model produced correct conclusions about evidence variability in all cases. Experiments 2 and 3 explored the effect of repeated learning trials on evidence variability in recognition and source memory tasks, respectively. Fits of the diffusion model supported the same conclusions about variability as the ROC literature. For recognition, evidence variability was higher for targets than for lures, but it did not differ on the basis of the number of learning trials for target items. For source memory, evidence variability was roughly equal for source 1 and source 2 items, and variability increased for items with additional learning attempts. These results demonstrate that RT modeling can help resolve ambiguities regarding the processes that produce different patterns in ROC data. The results strengthen the evidence that memory strength distributions have unequal variability across item types in recognition and source memory tasks.

Risk–benefit evaluation of on-line high-performance liquid chromatography analysis for pooling decisions in large-scale chromatography

In the production of a human therapeutic protein from inclusion bodies, product related impurities of very similar size and charge to the product are created as byproducts of the refold process. Their removal is usually challenging even when using chromatography with high performance resins and elution by shallow linear gradients. Additionally, performing this type of separation for commercial production adds increased complexity. To maximize productivity, columns are loaded so high that product elution profiles are not well separated from the impurities and pooling decisions are challenging. In this paper, conventional UV pooling based on fractionation or predefined absorbance based criteria will be compared to pooling based on fast on-line HPLC analytic. The development and implementation in a GMP process will be shown for a specific challenging separation by hydrophobic interaction chromatography. The different approaches have their unique complexities, timelines, uncertainties, and risks during development and implementation as well as during manufacturing. This study presents a probabilistic framework for quantitative comparison of two processes with unequal variability and uncertainty to evaluate the potential benefits of a PAT technology for its routine use in GMP Bioprocess manufacturing.

Evaluating the unequal-variance and dual-process explanations of zROC slopes with response time data and the diffusion model

We tested two explanations for why the slope of the z-transformed receiver operating characteristic (zROC) is less than 1 in recognition memory: the unequal-variance account (target evidence is more variable than lure evidence) and the dual-process account (responding reflects both a continuous familiarity process and a threshold recollection process). These accounts are typically implemented in signal detection models that do not make predictions for response time (RT) data. We tested them using RT data and the diffusion model. Participants completed multiple study/test blocks of an “old”/”new” recognition task with the proportion of targets and the test varying from block to block (.21, .32, .50, .68, or .79 targets). The same participants completed sessions with both speed-emphasis and accuracy-emphasis instructions. zROC slopes were below one for both speed and accuracy sessions, and they were slightly lower for speed. The extremely fast pace of the speed sessions (mean RT = 526) should have severely limited the role of the slower recollection process relative to the fast familiarity process. Thus, the slope results are not consistent with the idea that recollection is responsible for slopes below 1. The diffusion model was able to match the empirical zROC slopes and RT distributions when between-trial variability in memory evidence was greater for targets than for lures, but missed the zROC slopes when target and lure variability were constrained to be equal. Therefore, unequal variability in continuous evidence is supported by RT modeling in addition to signal detection modeling. Finally, we found that a two-choice version of the RTCON model could not accommodate the RT distributions as successfully as the diffusion model.

Poorly Treated or Unrecognized GERD Reduces Quality of Life in Patients with COPD

The effect of gastroesophageal reflux disease (GERD) on health-related quality of life (HRQL) in COPD has never been assessed. To evaluate HRQL in patients with COPD alone compared with those with both COPD and continuing GERD symptoms. A questionnaire-based, cross-sectional survey was performed. Subjects were recruited from the outpatient pulmonary clinics at the University of Florida Health Science Center/Jacksonville. Included patients had an established diagnosis of COPD. Exclusion criteria were respiratory disorders other than COPD, known esophageal disease, active peptic ulcer disease, Zollinger-Ellison syndrome, mastocytosis, scleroderma, and current alcohol abuse. Those meeting the criteria and agreeing to participate were asked to complete the Mayo Clinic GERQ and SF-36 questionnaires, by either personal or telephone interview. Clinically significant reflux was defined as heartburn and/or acid regurgitation weekly. Study patients were divided into two groups for HRQL analysis based on the GERQ response: COPD+/GERD+ and COPD only. Statistical analysis was performed using the Mann-Whitney-Wilcoxon T test for unequal variables and linear regression was performed using ANOVA. All data are expressed as mean and standard deviation. Eighty-six patients completed both questionnaires. Males were 55% and COPD+/GERD+ patients comprised 37% of the study group. Compared with COPD only, HRQL was reduced across all measures for the COPD+ GERD+ patients and achieved significance for bodily pain (P<0.02), mental health (P<0.05), and physical component score (P<0.05). Patients with COPD and continuing GERD symptoms have reduced HRQL in comparison with those with COPD alone.

Unequal group variances in microarray data analyses

In searching for differentially expressed (DE) genes in microarray data, we often observe a fraction of the genes to have unequal variability between groups. This is not an issue in large samples, where a valid test exists that uses individual variances separately. The problem arises in the small-sample setting, where the approximately valid Welch test lacks sensitivity, while the more sensitive moderated t-test assumes equal variance. We introduce a moderated Welch test (MWT) that allows unequal variance between groups. It is based on (i) weighting of pooled and unpooled standard errors and (ii) improved estimation of the gene-level variance that exploits the information from across the genes. When a non-trivial proportion of genes has unequal variability, false discovery rate (FDR) estimates based on the standard t and moderated t-tests are often too optimistic, while the standard Welch test has low sensitivity. The MWT is shown to (i) perform better than the standard t, the standard Welch and the moderated t-tests when the variances are unequal between groups and (ii) perform similarly to the moderated t, and better than the standard t and Welch tests when the group variances are equal. These results mean that MWT is more reliable than other existing tests over wider range of data conditions. R package to perform MWT is available at http://www.meb.ki.se/~yudpaw

Jacobi polynomials approximation to the one-speed neutron transport equation

Jacobi polynomials, the largest family of classical orthogonal polynomial sequence, are used to obtain eigenspectrum of one-speed neutron transport equation for strongly anisotropic scattering. Previously detailed Ultraspherical or Gegenbauer polynomials approximation including spherical harmonics, Chebyshev polynomials approximation of first and second kinds is a special case of Jacobi polynomials approximation in which the two variables of the Jacobi polynomials are equal. Eigenspectrum calculations using the so-called Jacobi polynomials approximation have demonstrated that plane symmetrical systems prefer Ultraspherical polynomials approximation since their well-known peculiarity or symmetry property meets the requirement of symmetry in angular flux with respect to spatial coordinates for every order of approximation. In the more general case when two variables of Jacobi polynomial are unequal, symmetry in eigenvalues disappear in the low-order approximations. However, it has been shown that symmetrical eigenvalue pairs are reached asymptotically as the order of approximation is increased for unequal variables too. Jacobi polynomials approximation is further applied to homogeneous slab criticality problem with strongly anisotropic scattering and reflected boundaries. Additionally, very useful analytical recursive relations for the calculation of various types of integrals involving Jacobi polynomials are derived which are needed in the eigenspectrum and criticality calculations.

Perfil socioeconômico e nutricional de pacientes com doença inflamatória intestinal internados em um hospital universitário

Inflammatory bowel diseases include chronic and relapsing inflammatory disorders, represented by ulcerative proctocolitis and Crohns disease, commonly associated with malnutrition. Characterize the nutritional and socioeconomic profile of patients hospitalized at the Pernambuco "Hospital das Clínicas", Recife, PE, Brazil. Cross-sectional study carried out at the gastroenterology clinic, which was previously approved by the Ethics Commission for studies involving human beings. The methods included clinical history data, socioeconomic conditions and nutritional assessment. Data were subject to statistical analysis (Students t test for equal and unequal variables). The sample consisted of 24 male and female patients, with a mean age of 43.83 +/- 16.13 years, mostly married, coming from Recife, with low income, who lived in their own house with relatives. We found a higher prevalence of ulcerative proctocolitis (62.5%), with diagnosis time of more than 5 years, symptoms of abdominal pain, bloody-mucous diarrhea with 6-9 evacuations/day, with the distal colon being the most affected part. Osteoporosis was present in 26.7% of cases. Nutritional status was assessed through the body mass index. The weight loss percentage corresponded to 41.7% and 70.8%, respectively, classified as malnourished, associated or not with high prevalence levels of anemia, hypoalbuminemia and hypocalcemia. Gender correlation evidenced higher triceps fold and arm circumference values in men. Despite the study limitations, data suggest relevant information about the occurrence of these diseases in the northeast of Brazil, as well as about its frequent association with important nutritional deficiencies.

A Simultaneous Optimization Method for the Structure and Composition Differences of a Mass Exchange Network

This article presents a new method to calculate the composition differences (ɛ) for targeting the minimum total annualized cost (TAC) of a mass exchange network (MEN), which is based on the combination of composition interval diagram (CID) with mathematical programming. The total cost target consists of the capital cost of the process units and the operating cost for mass separating agents (MSAs). The value of total cost varies considerably with the composition differences, so the values of ɛ should be optimized in order to obtain minimum TAC of a MEN. This article considers ɛ as a set of unequal variables for each equilibrium equation of a rich-lean stream pair, employing them to build the CID and mathematical model, which optimizes the structure and composition differences simultaneously. Two examples are applied to illustrate the proposed method and the results demonstrate that the approach introduced by this article is simpler and more convenient than the methods in previous literatures.

Adjustments for heterogeneous herd-year variances in a random regression model for genetic evaluations of Polish Black-and-White cattle

The study investigated the existence of heterogeneous variance in first-lactation daily milk yield of Polish Black-and-White cows across herds in different years. Bayesian Information Criterion was used to show that the model with unequal residual variances for different herd-years was more plausible than the model assuming equal variances. A method of adjusting phenotypic records was developed to account for unequal variability in herd-years. Factors used for the data adjustment considered variation of general residuals and residuals for specific herd-years. The size of herd-year was also taken into account. Varied power of corrections was used to analyze the effect of adjustment on estimated breeding values. The method was applied to daily milk records of 817,165 primiparous cows. The effectiveness of the data adjustment was evaluated by the analysis of differences between each bull's breeding value and its parental index. Data correction reduced the average difference and variance of differences between breeding values and parental indices. Accounting for the size of herd-year classes in correction factors improved the efficiency of heterogeneous variance adjustment.

Celebrity suicide: Did the death of Kurt cobain influence young suicides in Australia?

This study examined the total rate of suicide in Australia for young people (aged 15-19 and 20-24 years) for the 30 day period after the announcement of Kurt Cobain's suicide in 1994, comparing with the identical period for the previous five years and accounting for unequal variability in weekends, Mondays and public holidays. The 1994 rates for male suicides for both age groups were lower than for 1992 and 1993, and were more similar to the 1990 rates. Female rates showed a steady small decline over the five years, sustained in 1994. Rates overall showed a reduction in all of the first five, ten and fifteen day rates, compared with previous years. There was no evidence of any increase in deaths from gunshot, the method used by Cobain. The conclusion appears to be that this celebrity suicide had little impact on suicide in young persons in Australia. Possible reasons for this are discussed.

The location of the maximum of asymmetric two-sided Brownian motion with triangular drift

The argmax distribution in Bhattacharya and Brockwell (1976) is extended to branches with unequal scalings as well as drifts. Examples show how this distribution class in change point problems with unequal variability may provide better approximations for the MLE than the symmetrical limit in Yao (1987).

UNEQUAL VARIABLES: Let X Equal Research And Y Equal Pedagogy: Why the Professor Can't Teach: Mathematics and the Dilemma of University Education by Morris Kline

"UNEQUAL VARIABLES: Let X Equal Research And Y Equal Pedagogy: Why the Professor Can't Teach: Mathematics and the Dilemma of University Education by Morris Kline." Change: The Magazine of Higher Learning, 10(6), pp. 69–70

Efficient Estimation of the Relationship between Plot Size and the Variability of Crop Yields

The optimum size of plot in field experimentation depends on the relationship between fixed costs and costs varying with number of units, and on soil variability. Perhaps the most useful measure of soil heterogeneity yet devised is that of Smith [1938], who showed empirically that the logarithm of the variance between plots of a given size was linearly related to the logarithm of the size of the plot. In the present paper we consider only the relationship between size and variability. The objects of the paper are, firstly, to show how efficient estimates of the constants in this relationship may be determined, and secondly, to illustrate a general method of determining efficient linear estimates when the data are, as in the present instance, correlated and of unequal variability. Koch and Rigney [1951] demonstrated that the regression coefficient of the logarithm of variance on the logarithm of plot size could be estimated from experimental data in which treatment effects are present, as well as from the data of uniformity trials. They noted that Smith had recommended that, in estimating the regression coefficient fi, the variances of the different sized plots should be weighted by their respective degrees of freedom. In fact, since the variance estimates for different size of plot, both in uniformity trials and experimental data, are built up from common components, they are frequently highly correlated, so that a simple weighting by degrees of freedom is not accurate. Koch and Rigney point out this difficulty for experimental data, but do not seem to have realized that their arguments apply with equal force to uniformity trial data. The present paper presents a method of weighting observed variances