• Journal of Korean Society of Transportation
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• v.32 no.2
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• pp.83-92
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• 2014

Weather condition is one of the crucial factors affecting travelers' mode choice. Nevertheless, there are numerous indefinite traffic phenomena under various weather conditions. This study was conducted to verify the hypothesis that transit riderships decrease as precipitation increases. To clarify the relationship between precipitation and transit ridership, a seemingly unrelated regression model was employed with data such as daily precipitation and daily transit riderships of 3 transit modes (bus, metro, and shuttle bus) collected in Busan for recent 24 months. The estimation results show that transit riderships decreased as the daily precipitation increased when the daily precipitation is greater or equal to 10mm/day (0.169%, 0.101%, and 0.172% reduction in bus, metro, and shuttle bus riderships, respectively, when the daily precipitation increased by 1mm). When comparing the impact of precipitation on transit riderships by modes using a cross-equation parameter restriction test, the decrease in metro ridership is relatively insensitive to the change in precipitation. However, the negative coefficient of precipitation in the metro ridership estimation model indicates that the transit users in Busan may alter their mode to taxi or automobile and/or may give up the trip itself in bad weather condition.

• Journal of Korea Water Resources Association
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• v.47 no.9
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• pp.743-752
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• 2014

Delay time for groundwater recharge means the travel time from the bottom of soil layer to groundwater through vadose zone after infiltration from rainfall. As it is difficult to measure delay time, we suggested an empirical formula which is derived by using linear regression between altitude and delay time. For the regression analysis, 4 major gauging watersheds were chosen (Hancheon, Kangjeongcheon, Oedocheon, Cheonmicheon) with 18 measured groundwater level stations. To verify this empirical formula, derived equation from linear reservoir theory was applied to compute delay time and to compare estimated amounts of groundwater recharge using both methods. The result showed good agreement. Furthermore, if derived empirical formula would be linked with SWAT model, the spatial time delay effect in the watershed could be reflected properly.

• The Korean Journal of Applied Statistics
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• v.16 no.2
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• pp.407-426
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• 2003

We consider the missing covariates problem in generalized estimating equations(GEE) model. If the covariate is partially missing, GEE can not be calculated. In this paper, we study the performance of 7 imputation methods to handle missing covariates in GEE models, and the properties of GEE estimators are investigated after missing covariates are imputed for ordinal data of repeated measurements. The 7 imputation methods include i) Naive Deletion ii) Sample Average Imputation iii) Row Average Imputation iv) Cross-wave Regression Imputation v) Carry-over Imputation vi) Bayesian Bootstrap vii) Approximate Bayesian Bootstrap. A Monte-Carlo simulation is used to compare the performance of these methods. For the missing mechanism generating the missing data, we assume ignorable nonresponse. Furthermore, we generate missing covariates with or without considering wave nonresp onse patterns.

• Journal of the Korean Data and Information Science Society
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• v.27 no.3
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• pp.689-700
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• 2016

We study estimation and inference of the joint conditional distributions of bivariate longitudinal outcomes using regression models and copulas. For the estimation of marginal models we consider a class of time-varying transformation models and combine the two marginal models using nonparametric empirical copulas. Regression parameters in the transformation model can be obtained as the solution of estimating equations and our models and estimation method can be applied in many situations where the conditional mean-based models are not good enough. Nonparametric copulas combined with time-varying transformation models may allow quite flexible modeling for the joint conditional distributions for bivariate longitudinal data. We apply our method to an epidemiological study of repeatedly measured bivariate cholesterol data.

• 한국노년학
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• v.41 no.3
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• pp.421-444
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• 2021

The purpose of this research is to examine the reciprocal relationships between depression and marital satisfaction among older couples. For longitudinal dyadic analysis, this study sets up a research model based on the Actor-Partner Interdependence Model, the Common Fate Model, and Autoregressive Cross-Lagged Model. Data came from four annual waves from the 10th year (2015) to the 13th year (2018) of the Korean Welfare Panel Survey and the final sample comprised a total of 1,383 married couples over 60 years of age in 2015. Structural Equation Modeling identified the reciprocal relationship between depression and marital satisfaction among older couples, with higher marital satisfaction of older couples leading to lower depression of husbands' and wives', and with higher depression of husbands' and wives' inducing lower marital satisfaction of the couples. Thus, this study suggested that longitudinal interplay between depression and marital satisfaction can lead to a vicious cycle. Based on these findings, the need to intervene at both the individual level and the couple level was discussed in order to reduce depression and improve marital satisfaction.

• Magazine of the Korean Society of Agricultural Engineers
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• v.32 no.4
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• pp.27-43
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• 1990

This study aimed at developing a generalized model on the estimation of the long - term run - off volume for practical purpose. During the research period of last 3 years( 1986-1988), 3 types of estimation model on the long - term run - off volume(Effective rainfall model, unit hydrograph model and barne's model for dry season) had been developed by the author. In this study, through regressional analysis between determinant factors (bi of effective rainfall model, ai of unit hydrograph model and Wi of barne's model) and catchment characteris- tics(catchment area, distance round the catchment area, massing degree coefficient, river - exte- nsion, river - slope, river - density, infiltration of Watershed) of 11 test case areas by multiple regressional method, a new methodology on the derivation of determinant factors from catchment characteristics in the watershed areas having no hydrological station was developed. Therefore, in the resulting step, estimation equations on run - off volume for practical purpose of which input facor is only rainfall were developed. In the next stage, the derived equations were applied on the Kang - and Namgye - river catchment areas for checking of their goodness. The test results were as follows ; 1. In Kang - river area, average relative estimation errors of 72 hydrographs and of continuous daily run - off volume for 245 days( 1/5/1982 - 31/12) were calculated as 6.09%, 9.58% respectively. 2. In Namgye - river area, average relative estimation errors of 65 hydrographs and of conti- nuous daily run - off volume for 2fl days(5/4/1980-31/12) were 5.68%, 10.5% respectively. In both cases, relative estimation error was averaged as 7.96%, and so, the methodology in this study might be hetter organized than Kaziyama's formula when comparing with the relative error of the latter, 24~54%. However, two case studies cannot be the base materials enough for the full generalization of the model. So, in the future studies, many test case studies of this model should he carries out in the various catchment areas for making its generalization.

• The Korean Journal of Applied Statistics
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• v.29 no.6
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• pp.1129-1145
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• 2016

Functional neuro-connectivity is one of the main issues in brain science in the sense that it is closely related to neurodynamics in the brain. In the paper, we choose fMRI as a main form of response data to brain activity due to its high resolution. We review methods for analyzing functional neuro-connectivity assuming that measurements are made on physiological responses to neuron activation. This means that we deal with a state-space and measurement model, where the state-space model is assumed to represent neurodynamics. Analysis methods and their interpretation should vary subject to what was measured. We included analysis results of real fMRI data by applying a high-dimensional autoregressive model, which indicated that different neurodynamics were required for solving different types of geometric problems.

• Journal of the korean academy of Pediatric Dentistry
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• v.29 no.1
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• pp.115-124
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• 2002

The purpose of this study was to establish regression equations and probability charts for predicting the sum of mesiodistal crown diameters of unerupted unilateral canine and premolars from the sum of mesiodistal crown diameters of four mandibular incisors in Korean male and female. The plaster casts of 162 children(75 boys and 87 girls) among the contestees in 1994-2001 Healthy Dentition Contest in Seoul were measured. Sex differences are compared and the following results were obtained: 1. Bilateral comparison of sum of widths of permanent canine and premolars showed no significant differences for either sex(p>0.05). Sum of widths of permanent canine and premolars of male were significantly larger than that of female(p<0.01). 2. Regression equations for the prediction of sum of widths of permanent canine and premolars in each sex were as follows Male ${\Sigma}Maxillary$ 345 y= 10.45+0.53x Male ${\Sigma}Mandibular$ 345 : y= 10.07+0.51x Female ${\Sigma}Maxillary$ 345 : y=12.65+0.42x Female ${\Sigma}Mandibular$ 345 : y=11.70+0.42x Male+female ${\Sigma}Maxillary$ 345 y=11.01+0.50x Male+female ${\Sigma}Mandibular$ 345 : y=9.87+0.51x

• The Mathematical Education
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• v.46 no.4
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• pp.407-421
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• 2007

The purpose of this study is to identify the item characteristics that are supposed to affect item difficulty and to estimate the regression equations for predicting item difficulty of mathematics in the College Scholastic Ability Test(CSAT). We selected six variables related to item characteristics based on learning theories: contents, cognitive domain, novelty, item type, number of concepts, and the amount of computation. With data of the CSAT mathematics test administered in 2004-2006, item difficulty was regressed on the six variables, the location of an item, and the item writer's judgment on difficulty. The novelty of an item was found to be a statistically insignificant variable in explaining item difficulty. Four regression equations with different sets of independent variables could explain $70%{\sim}80%$ of the item difficulty variance and were validated as predicting item difficulty of the mock CSAT in 2006.

• Journal of Animal Science and Technology
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• v.52 no.2
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• pp.157-164
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• 2010

We investigated the influence of carcass traits on carcass price for Hanwoo cow using multiple regression and path analyses. Data for carcass traits and price were collected on mature Hanwoo cow raised in private farms in Kangwon province that were slaughtered in 2008. A total of 96 animals with the average slaughter age of 51 months were used in the current study. Of the carcass traits studied, marbling score (MAR), dressing percentage (DP), and eye-muscle area (EMA) showed moderate and positive correlations with auction price (AP), while correlation coefficients of meat yield index (MINDEX) with AP were low or even negligible. In multiple regression analyses of AP and carcass price (CP) on cold carcass weight (CWT), back fat thickness (BFT), EMA, MAR, and DP, estimates of $R^2$ were 69.86 and 85.43%, respectively. Partial regression coefficients for CWT, BFT, EMA, MAR and DP were -0.028, -0.106, 0.107, 0.814, and 0.075 in the equation of AP and 0.561, -0.060, 0.083, 0.590, and 0.051 in the equation of CP. In path analyses, MAR's total contribution on the variation of AP was largest (0.667), and the total contributions of MAR and CWT on the variation of CP were 0.403 and 0.397. The current study suggested that marbling was the most influential trait on the variation of auction price, and marbling and cold carcass weight were critical traits on the variation of carcass price.