• Journal of Auto-vehicle Safety Association
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• v.14 no.1
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• pp.62-67
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• 2022

This study is to construct the simple estimating model for the HIC15 of the driver dummy using the frontal impact test results. Test results of 9 vehicles of Hyundai Sonata from the MY2002~MY2020 USNCAP are utilized for constructing the linear regression model. The average accelerations extracted from the vehicle crash pulses are handled as the main factors. The average accelerations of 10 ms interval within 0~100 ms are calculated from the crash pulse data of 9 vehicles. The present estimating model of the HIC15 using the average accelerations of 10 ms interval in the 0~80 ms range shows good agreement with the tested value within 2.4% maximum error.

• Physical Therapy Korea
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• v.8 no.3
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• pp.63-76
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• 2001

Many studies have shown that the initial median frequency (MDF) and slope correlate with the muscle fiber composition. This study tested the hypothesis that the initial MDF and slope are fixed, regardless of the interval at which data are collected. MDF data using moving fast Fourier transformation of EMG signals, following local fatigue induced by isotonic exercise, were obtained. An inverse FFT was used to eliminate noise, and characteristic decreasing regression lines were obtained. The regression analysis was done in three different periods, the first one third, first half, and full period, looking at variance in the initial MDF, slope, and fatigue index. Data from surface EMG signals during fatiguing isotonic exercise of the biceps brachii and vastus lateralis in 20 normal subjects were collected. The loads tested were 30% and 60% maximum voluntary contraction (MVC) in the biceps brachii and 40% and 80% MVC in the vastus lateralis. The rate was 25 flexions per minute. There were no significant differences in the initial MDF or slope during the early or full periods of the regression, but there was a significant difference in the fatigue index. Therefore, to observe the change in the initial MDF and slope of the MDF regression line during isotonic exercise, this study suggest that only the early interval need to be observed.

• Journal of Families and Better Life
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• v.10 no.1 s.19
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• pp.131-138
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• 1992

Regression analysis has become a standard statistical tool in the behavioral science. Because of its widespread popularity. regression has been often misused. Such is the case when the dependent variable is a qualitative measure rather than a continuous, interval measure. Regression estimates with a qualitative dependent variable does not meet the assumptions underlying regression. It can lead to serious errors in the standard statistical inference. Logit model is recommended as alternatives to the regression model for qualitative dependent variables. Researchers can employ this model to measure the relationship between independent variables and qualitative dependent variables without assuming that logit model was derived from probabilistic choice theory. Coefficients in logit model are typically estimated by the method of Maximum Likelihood Estimation in contrast to ordinary regression model which estimated by the method of Least Squares Estimation. Goodness of fit in logit model is based on the likelihood ratio statistics and the t-statistics is used for testing the null hypothesis.

• The Korean Journal of Applied Statistics
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• v.29 no.7
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• pp.1311-1327
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• 2016

We propose a multi-state model for analyzing semi-competing risks data with interval-censored or missing intermediate events. This model is an extension of the 'illness-death model', which composes three states, such as 'healthy', 'diseased', and 'dead'. The state of 'diseased' can be considered as an intermediate event. Two more states are added into the illness-death model to describe missing events caused by a loss of follow-up before the end of the study. One of them is a state of 'LTF', representing a lost-to-follow-up, and the other is an unobservable state that represents the intermediate event experienced after LTF occurred. Given covariates, we employ the Cox proportional hazards model with a normal frailty and construct a full likelihood to estimate transition intensities between states in the multi-state model. Marginalization of the full likelihood is completed using the adaptive Gaussian quadrature, and the optimal solution of the regression parameters is achieved through the iterative Newton-Raphson algorithm. Simulation studies are carried out to investigate the finite-sample performance of the proposed estimation procedure in terms of the empirical coverage probability of the true regression parameter. Our proposed method is also illustrated with the dataset adapted from Helmer et al. (2001).

• Asian-Australasian Journal of Animal Sciences
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• v.11 no.4
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• pp.363-367
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• 1998

This study has objectives of to estimate the genetic and phenotypic trend for growth in a closed herd of Landrace $\times$ desi crossbreds. The possibility of early selection of boars was also investigated in order to reduce generation interval and thus, to enhance response per year in selection programmes. The data originated from Livestock Production Research (Pigs), Indian Veterinary Research Institute (IVRI), Izatnagar (UP), India - a unit of All India Coordinated research Project on Pigs (AICRP on Pigs). Data consisted of 891 crossbred piglets, progeny of 29 boars. The piglets were born in 132 parities of 72 sows between 8 years from 1987 to 1994. Records on weight at birth, at 2 weeks interval upto 8 weeks of age (Wl, W2, ${\cdots}\;{\cdots}$ W8) and at 16th week (W16) were used in this investigation. BLLTP estimates of the sires were computed. Breeding value of each sire was estimated as twice of sire and sire group solutions. Phenotypic trend was estimated as regression of weight performance on year. Genetic trend was computed by estimating regression of breeding value of sires on time. Average body weights ranged from 0.92 kg (W1) to 18.95 kg (W16) and showed a continuous increase over age. Heritabilities of the weight at 4th and 6th week were medium (0.29 and 0.14). Rest of the weights were highly heritable. The product moment and rank, both correlations were high between breeding value for W6 and W16 (0.68 and 0.70). This shows that sire selection for W6 can be successfully implemented in order to achieve sufficient genetic improvement in growth. Phenotypic trend was positive at all ages. The phenotypic regression coefficient ranged from 0.02 kg at birth to 0.40 kg at 16 weeks. Genetic trend was also positive. The regression coefficients of average breeding value of sires on time showed a range of 1.471 kg (0.021 to 1.492 kg) for different weights. These coefficients were significant and higher than their corresponding phenotypic regression coefficient.

• The Korean Journal of Applied Statistics
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• v.12 no.2
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• pp.449-461
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• 1999

본 논문에서는 패널회귀모형에서 내부변환(within transformation) 추정량을 이용하여 회귀계수에 대한 정확한 신뢰구간을 제시하였다. 아울러 이러한 신뢰구간의 효율성을 신뢰계수(confidence coefficient)와 신뢰구간의 평균길이(average length of confidence interval)을 사용하여 모의실험을 통하여 다른 근사적 신뢰구간들과 비교하였다. 실험결과, 내부변환추정량을 이용한 신뢰구간은 다른 근사적 신뢰구간들에 비해 명목신뢰계수를 정확히 유지하였고, 신뢰구간의 평균길이도 다른 방법들에 비해 짧은 결과를 보았다.

• Journal of the Korean Data and Information Science Society
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• v.13 no.2
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• pp.271-284
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• 2002

In this paper we consider the robust inference for the parameter of linear regression model based on weighted least squares. First we consider the sequential test of multiple outliers. Next we suggest the way to assign a weight to each observation $(x_i,\;y_i)$ and recommend the robust inference for linear model. Finally, to check the performance of confidence interval for the slope using proposed method, we conducted a Monte Carlo simulation and presented some numerical results and examples.

• Proceedings of the Korean Statistical Society Conference
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• 2003.05a
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• pp.75-78
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• 2003

Those who are interested in making inferences concerning linear combination of variance components in a simple linear regression model with unbalanced nested error structure can use the confidence intervals proposed in this paper. Two approximate confidence intervals for the sum of two variance components in the model are proposed. Simulation study is peformed to compare the methods.

• The Korean Journal of Applied Statistics
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• v.17 no.1
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• pp.145-151
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• 2004

PROC MIXED fits a variety of mixed models to data and enables one to use these fitted models to make statistical inferences about the data. However, the simulation study in this article shows that PROC MIXED using REML estimators provides one with a confidence interval, that does not keep the stated confidence coefficients, on sums of two variance components in the simple regression model with unbalanced nested error structure which is a mixed model.

• Journal of Veterinary Clinics
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• v.27 no.4
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• pp.427-434
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• 2010

Correlation is a technique used to measure the strength or the degree of closeness of the linear association between two quantitative variables. Common misuses of this technique are highlighted. Linear regression is a technique used to identify a relationship between two continuous variables in mathematical equations, which could be used for comparison or estimation purposes. Specifically, regression analysis can provide answers for questions such as how much does one variable change for a given change in the other, how accurately can the value of one variable be predicted from the knowledge of the other. Regression does not give any indication of how good the association is while correlation provides a measure of how well a least-squares regression line fits the given set of data. The better the correlation, the closer the data points are to the regression line. In this tutorial article, the process of obtaining a linear regression relationship for a given set of bivariate data was described. The least square method to obtain the line which minimizes the total error between the data points and the regression line was employed and illustrated. The coefficient of determination, the ratio of the explained variation of the values of the independent variable to total variation, was described. Finally, the process of calculating confidence and prediction interval was reviewed and demonstrated.