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The statistical field of survival analysis focuses on the examination of time-to-event data. The proportional hazards (PH) model is the most widely used in multivariate survival analysis to examine the effects of various factors on survival time. The statistics, however, do not always support the PH models assumption of constant hazards. The power of the associated statistical tests is reduced when the PH assumption is broken, which leads to incorrect interpretation of the estimation results. The accelerated failure time (AFT) models, on the other hand, do not, like the PH model, assume constant hazards in the survival data. Additionally, the AFT models can be employed in place of the PH model if the constant hazards assumption violated. This study set out to examine how well the PH model and the AFT models performed when it came to identifying the proximate variables influencing under – five mortality from National Family Health Survey data in Uttar Pradesh. Three AFT models that were based on the Weibull, exponential, and log-normal distributions were the only ones discussed in this article. The research employing a graphical technique and a statistical test revealed that the NFHS-5 data set has non-proportional hazards. The log-normal AFT model was the most acceptable model among the ones studied, according to the Akaike information criterion (AIC).
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The objective is to deal with brain effective connectivity among epilepsy electroencephalogram (EEG) signals recorded by use of depth electrodes in the cerebral cortex of patients suffering from refractory epilepsy during their epileptic seizures. The Wiener-Granger Causality Index (WGCI) is a well-known effective measure that can be useful to detect causal relations of interdependence in these kinds of EEG signals. It is based on the linear autoregressive model, and the issue of the estimation of the model parameters plays an important role in the calculation accuracy and robustness of WGCI to do research on brain effective connectivity. Focusing on this issue, a modified Akaike's information criterion algorithm is introduced in the computation of the WGCI to estimate the orders involved in the underlying models and in order to advance the performance of WGCI to detect brain effective connectivity. Experimental results support the interesting performance of the proposed algorithm to characterize the information flow both in a linear stochastic system and a physiology-based model.
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RESUMEN La captura promedio anual de la pesquería de la jaiba azul (Callinectes sapidus) (JA) en Tamaulipas, México se estima en 2 733 T, de la cual, el 82 % se pesca en la Laguna Madre, sitio que se considera aprovechado al máximo de su capacidad. El objetivo de la presente investigación fue modelar la captura anual de la JA en la Laguna Madre, Tamaulipas, mediante el ajuste de funciones matemáticas de tipo lineal y no lineal (o curvilínea), a la serie de tiempo de 1998 a 2012, además de identificar las fases de desarrollo de la pesquería, de acuerdo a varios modelos generalizados. Se utilizó el enfoque de la teoría de la información y el procedimiento de la inferencia multimodelo (IMM). Se ajustaron 11 modelos de regresión lineal y no lineal. Para la selección de modelos se utilizaron los criterios de información Akaike corregido (CIAc) y bayesiano (CIB). Para el IMM se consideró el nivel ∆i <2de plausibilidad de CIAc y CIB. Los modelos elegidos para el IMM fueron compuesto, crecimiento, exponencial, logístico, potencial y el sigmoideo, considerándose como más adecuados los primeros cuatro modelos citados. Los modelos promedio del IMM presentaron valores de β 0 y β 1 de 0.939 y 0.377 respectivamente, según CIAc; y de 0.952 y 0.344 respectivamente, de acuerdo al CIB. Solo los modelos compuesto y logístico mostraron significancia estadística en sus dos parámetros de regresión (β 0 y β 1). El índice de sustentabilidad pesquera reveló seis periodos de la captura y una disminución en magnitud de los cambios de la captura. La serie de datos analizada incluye dos ciclos de vida de acuerdo a los modelos de Csirke y Caddy. Los resultados mostraron que al final del periodo estudiado la pesquería se encontraba en colapso y decadencia.
ABSTRACT The average annual catch of the blue crab (Callinectes sapidus) (BC) fishery in Tamaulipas, Mexico is estimated at 2 733 T, of which the 82 % is caught in the Laguna Madre, which is considered to be exploited to the maximum of its capacity. The objective of the present investigation was to model the annual catch of the BC in the Laguna Madre, Tamaulipas, by adjusting mathematical functions of the linear and nonlinear (or curvilinear) type, to the time series from 1998 to 2012. In addition, the phases of development of the fishery, according to several generalized models, were identified. We used the information theory approach and multimodel inference procedure (MMI). Eleven linear and nonlinear regression models were fitted. For the selection of models, the corrected Akaike corrected (AICc) and Ba-yesian (BIC) information criteria were used. For the MMI, the level ∆i < 2 of plausibility of AICc and BIC was considered. The models chosen for the MMI were compound, growth, exponential, logistic, potential and the sigmoid, with the first four models being considered the most suitable of all those cited. The average models of the MMI presented values of β 0 and β 1: 0.939 and 0.377 respectively, according to CIAc; and 0.952 and 0.344 respectively, according to the CIB. Only the composite and logistic models showed statistical significance in their two regression parameters (β 0 and β 1). The fishery sustainability index revealed six catch periods and a decrease in magnitude of catch changes. The data series analyzed includes two life cycles according to the Csirke and Caddy models. The results showed that at the end of the studied period the fishery was in collapse and decay.
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Background: Type 2 diabetes mellitus (T2DM) disease has become public health concern, because of its increasing rate worldwide especially in developing countries. Previous studies have used statistical methods like multiple regression and correlation to show factors associated with Quality of life (QoL) assessed by SF-36 despite the scoring nature of the items. This study aimed at identifying best model and factors associated with gender differentials in QoL among T2DM. Methods: This cross-sectional study recruited T2DM from Diabetes Care Centre of a teaching hospital, South-western, Nigeria. The models considered were Poisson Model with log link function and square-root link function. The model selection criteria used was Akaike Information Criterion (AIC). The model with the smaller AIC was considered to be better. Results: The AIC values for Poisson model with log and square-root link functions for Physical Component Summary (PCS) were 1713 and 1708.3, Mental Component Summary (MCS): 1482.2 and 1480.7, QoL: 2359.7 and 235.8 respectively. Age and diastolic blood pressure had significant negative association with PCS, MCS and QoL in both gender (p<0.05), while occupation and education had significant positive association with PCS, MCS and QoL more in male than female. BMI of normal weight had significant reduction in PCS and QoL of female, whereas this had significant increase in the MCS of male. Conclusion: Poisson model with square-root link function was of better fit to model QoL in T2DM. The significant positive effect of occupation and education on QoL and its domains was more in male than female.
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Milk yield records (305d, 2X, actual milk yield) of 123,639 registered first lactation Holstein cows were used to compare linear regression (y = β0 + β1X + e) ,quadratic regression, (y = β0 + β1X + β2X2 + e) cubic regression (y = β0 + β1X + β2X2 + β3X3 + e) and fixed factor models, with cubic-spline interpolation models, for estimating the effects of inbreeding on milk yield. Ten animal models, all with herd-year-season of calving as fixed effect, were compared using the Akaike corrected-Information Criterion (AICc). The cubic-spline interpolation model with seven knots had the lowest AICc, whereas for all those labeled as "traditional", AICc was higher than the best model. Results from fitting inbreeding using a cubic-spline with seven knots were compared to results from fitting inbreeding as a linear covariate or as a fixed factor with seven levels. Estimates of inbreeding effects were not significantly different between the cubic-spline model and the fixed factor model, but were significantly different from the linear regression model. Milk yield decreased significantly at inbreeding levels greater than 9 percent. Variance component estimates were similar for the three models. Ranking of the top 100 sires with daughter records remained unaffected by the model used.
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Animales , Bovinos/genética , Industria Lechera , Lactancia , Producción de Alimentos , EndogamiaRESUMEN
We evaluated the efficacy of chotosan for headache patients via multiple regression analysis. The subjects were 46 patients with headache (31 migraine, 14 tension-type, and1combination headache), consisting of 1 3males and 33 females, mean age 48 years (range 19-77 years), who were treated with chotosan according to their Sho (symptoms) for more than1month. The relationships between the improvement of headache and 38 factors, including age, sex, height, body weight, hypertension and other symptoms noted upon first medical examination, were examined through multi-dimensional cross-sectional analysis. Morning headache, dizziness, insomnia, body weight, tinnitus and vasodilatation of sublingual veins were significant factors. Morning headache is traditionally an indication for the use of chotosan, and our results support its efficacy for this purpose. Three factors, i.e. morning headache, vasodilatation of sublingual veins and stiff shoulder, were the best subset of explanatory variables. Stiff shoulder is a key symptom for the application of chotosan, while stiffness in the back is a key symptom for the application of yokukansan.
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CefaleaRESUMEN
We evaluated the efficacy of yokukansan-based prescriptions for patients with headache. Forty-five patients with headache (34 migraine, 6 tension-type, and 5 combined headaches), or 6 males and 39 females, mean age 38 (25 to 68) years were treated with yokukansan-based prescriptions according to their Sho diagnosis, for 1 to 24 months. Relationships between headache improvement, and 31 factors including age, sex, height, body weight and other symptoms at first examination, were qualified with multi-dimensional analysis. Factors such as painful eye sensation, back stiffness, eyestrain and irritability were significant indicators of headache improvement. Three of these factors (painful eye sensation, back stiffness and irritability) were the best subset of explanatory variables. Yokukansan-based prescriptions seemed to be effective for “liver-related” headache, and were thought to be useful to relieve a triggering or worsening of headache factors. And to our knowledge, this is the first paper to propose the importance of examinations of the back, when considering yokukansan-based prescriptions.
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Cefalea , Dorso , PrescripcionesRESUMEN
The purpose of this paper is to propose a two dimensional power-normal transformation model to detect the circadian rhythm of blood pressure. Our model is an extension of that proposed by Uragari et al In the proposed model, we consider the correlation between systolic and diastolic blood pressures, and check the influence of the truncated data distribution after the Box-Cox transformation. An application is given to the data obtained from a clinical phase-one study of a Kampo formulation. We also discuss the necessity of evaluating the effects of Kampo formulations on the circadian rhythm of blood pressure.
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For the evaluation of the efficacy in a long-term treatment with a Kampo prescription, it is important to analyze repeated measurements based on their time course patterns.<br>In this paper, we analyze from the point of model selection with AIC the repeated measurements of platelet obtained from 24 Idiopathic Thrombocytopenic Purpura patients treated with a Kampo prescription (Sho-saiko-to) for 1 year. With the results, we analyze the repeated measurements obtained from another 6 patients of the same disease.
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In many clinical studies to evaluate the efficacy of Kampo prescriptions, subjects are selected because they have high or low values of the characteristics of interest, such as blood pressure or serum cholesterol, and the data obtained from the subjects before and after treatment are analyzed. In such analyses, we should take into account the possible changes in the observations due to regression toward the mean, otherwise the results of the analyses will be incorrect.<br>In this paper, we consider the effect of regression toward the mean in analyzing data and propose a method of analysis with Akaike Information Criterion (AIC) to avoid incorrect results.
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It is well known that there exist inter-individual variations in the pharmacokinetics of pharmaceutical components in Kampo prescriptions. In the area of Kampo medicine, however, there have so far been no reports on the analysis by introducing these variations.<br>In this paper, from the perspective of population pharmacokinetics, we analyze the data of plasma concentration of ephedrine obtained from 8 healthy male volunteers after single oral administration of Sho-seiryu-to (extract) by introducing the inter-individual variations.<br>On the results, we simulate the plasma concentration in multiple oral administrations.