• Child Health Nursing Research
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• v.22 no.2
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• pp.79-86
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• 2016

Purpose: The purpose of this study was to identify breastfeeding practice with late preterm infants (LPIs), and to determine predictors of exclusive breastfeeding at the 12th week after discharge. Methods: The participants were 106 mothers of LPIs hospitalized in neonatal intensive care units at two university hospitals. Data were collected between February and October, 2013. Questionnaires included characteristics of LPIs, their mothers, and feeding-related characteristics. Feeding methods were exclusive breastfeeding, mixed feeding, and formula feeding. Results: Exclusive breastfeeding steadily increased from 5.7% at the 1st week to 19.8% at the 12th week, as did formula feeding from 27.3% to 67.9%. Contrarily, mixed feeding decreased from 67.0% at the 1st week to 12.3% at the 12th week. The ratio of formula feeding was higher than that of exclusive breastfeeding over time. Predictors for exclusive breastfeeding were the following: type of delivery (OR=2.96, 95%CI=1.07-8.14), feeding intolerance (OR=3.03, 95%CI=1.26-7.25) and feeding method during hospitalization (OR=7.84, 95%CI=3.15-19.53). Conclusion: In order to increase breastfeeding opportunities for LPIs, educational programs for gestational age-appropriate breastfeeding should be developed. The focus of breastfeeding education needs to be on mothers who delivered their LPIs through Cesarean-section and LPIs who had feeding intolerance or were fed only formula during hospitalization.

• Journal of Medicine and Life Science
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• v.20 no.4
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• pp.166-171
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• 2023

Mixed urinary incontinence (UI) is common in women. This study aimed to assess the efficacy of anti-incontinence surgery in female patients with equally severe stress UI (SUI) and urge UI (UUI). All patients had equal severity of SUI and UUI. The postoperative cure rate was categorized into the cure group (CG) and failure group (FG). Postoperative satisfaction was categorized into the satisfaction group (SG) and the dissatisfaction group (DG). Statistical significance was set at P<0.05. Ninety patients (SG, 73.3%; DG, 26.7%; CG, 93.3%; FG, 6.7%) were included in the study. In the univariate analysis, body mass index (BMI), total bladder capacity, and overactive bladder symptom score (OABSS) were significantly different between the SG and DG groups. Peak urinary flow, Valsalva leak point pressure (VLPP), and OABSS were significantly different between the CG and FG groups. In the multivariate analysis, OABSS (P=0.001) and BMI (P=0.032) were independent predictors of postoperative satisfaction. VLPP (P=0.023) was the only independent factor associated with the postoperative cure rate. In equal severity of SUI and UUI, VLPP was found to be the only independent factor associated with postoperative cure rates. Higher VLPP values were associated with higher cure rates. BMI and OABSS were identified as independent predictors of postoperative satisfaction, with lower BMI and OABSS associated with higher postoperative satisfaction.

• Communications for Statistical Applications and Methods
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• v.10 no.3
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• pp.845-857
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• 2003

We explore the use of genetic programming to evolve decision trees directly for classification problems with both discrete and continuous predictors. We demonstrate that the derived hypotheses of standard algorithms can substantially deviated from the optimum. This deviation is partly due to their top-down style procedures. The performance of the system is measured on a set of real and simulated data sets and compared with the performance of well-known algorithms like CHAID, CART, C5.0, and QUEST. Proposed algorithm seems to be effective in handling problems caused by top-down style procedures of existing algorithms.

• The korean journal of orthodontics
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• v.53 no.2
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• pp.106-115
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• 2023

Objective: To evaluate the null hypothesis that there is no difference in a set of clinical predictors of potentially impacted canines between low-risk patients with and without displaced canines. Methods: The normal canine position group consisted of 30 patients with 60 normally erupting canines ranked in sector I (age, 9.30 ± 0.94 years). The displaced canine group comprised 30 patients with 41 potentially impacted canines ranked in sectors II to IV (age, 9.46 ± 0.78 years). Maxillary lateral incisor crown angulation, inclination, rotation, width, height, and shape, as well as palatal depth, arch length, width, and perimeter composed a set of clinical predictors, which were evaluated on digital dental casts. Statistical analyses consisted of group comparisons and variable correlations (p < 0.05). Results: There was a significant association between sex and mesially displaced canines. Unilateral canine displacement was more prevalent than bilateral displacement. The crown of the maxillary lateral incisors was significantly angulated more mesially and rotated mesiolabially in low-risk patients with displaced canines, who also had a shallower palate and shorter anterior dental arch length. Lateral incisor crown angulation and rotation, as well as palatal depth and arch length, were significantly correlated with the canine displacement severity. Conclusions: The null hypothesis was rejected. Maxillary lateral incisor angulation inconsistent with the "ugly duckling" stage as well as a shallow palate and short arch length are clinical predictors that can significantly contribute to the early screening of ectopic canines in low-risk patients.

• Communications for Statistical Applications and Methods
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• v.30 no.1
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• pp.65-73
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• 2023

Contemporary biomedical data often involve an ill-posed problem owing to small sample size and large number of multi-collinear variables. Partial least squares (PLS) method could be a plausible alternative to an ill-conditioned ordinary least squares. However, in the case of a PLS model that includes a random-effect, how to deal with a random-effect or mixed effects remains a widely open question worth further investigation. In the present study, we propose a modified multivariate PLS method implementing mixed-effect model (PLSM). The advantage of PLSM is its versatility in handling serial longitudinal data or its ability for taking a randomeffect into account. We conduct simulations to investigate statistical properties of PLSM, and showcase its real clinical application to predict treatment outcome of esthetic surgical procedures of human faces. The proposed PLSM seemed to be particularly beneficial 1) when random-effect is conspicuous; 2) the number of predictors is relatively large compared to the sample size; 3) the multicollinearity is weak or moderate; and/or 4) the random error is considerable.

• Asian-Australasian Journal of Animal Sciences
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• v.13 no.3
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• pp.413-422
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• 2000

In the class of models which include random effects, the variance component estimates are important to obtain accurate predictors and estimators. Variance component estimation is straightforward for balanced data but not for unbalanced data. Since orthogonality among factors is absent in unbalanced data, various methods for variance component estimation are available. REML estimation is the most widely used method in animal breeding because of its attractive statistical properties. Recently, Bayesian approach became feasible through Markov Chain Monte Carlo methods with increasingly powerful computers. Furthermore, advances in variance component estimation with complicated models such as generalized linear mixed models enabled animal breeders to analyze non-normal data.

• Journal of the Korean Statistical Society
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• v.28 no.2
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• pp.225-234
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• 1999

We consider the following semi-parametric non-linear mixed effect regression model : y\ulcorner=f($\chi$\ulcorner;$\beta$)+$\sigma$$\mu$($\chi$\ulcorner)+$\sigma$$\varepsilon$\ulcorner,i=1,…,n,y*=f($\chi$;$\beta$)+$\sigma$$\mu$($\chi$) where y'=(y\ulcorner,…,y\ulcorner) is a vector of n observations, y* is an unobserved new random variable of interest, f($\chi$;$\beta$) represents fixed effect of known functional form containing unknown parameter vector $\beta$\ulcorner=($\beta$$_1$,…,$\beta$\ulcorner), $\mu$($\chi$) is a random function of mean zero and the known covariance function r(.,.), $\varepsilon$'=($\varepsilon$$_1$,…,$\varepsilon$\ulcorner) is the set of uncorrelated measurement errors with zero mean and unit variance and $\sigma$ is an unknown dispersion(scale) parameter. On the basis of finite-sample, small-dispersion asymptotic framework, we derive an absolute lower bound for the asymptotic mean squared errors of prediction(AMSEP) of the regular-consistent non-linear predictors of the new random variable of interest y*. Then we construct an optimal predictor of y* which attains the lower bound irrespective of types of distributions of random effect $\mu$(.) and measurement errors $\varepsilon$.

• Phonetics and Speech Sciences
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• v.9 no.1
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• pp.19-26
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• 2017

The main objective of this study is to investigate the influence of utterance internal pause in English speaking evaluation. To avoid possible confusion with other errors caused by segmental and prosodic inaccuracy, stem utterances with two different length obtained from a native speaker were manipulated to make a set of stimuli tokens through insertion of pauses whose length and position vary. After a total of 90 participants classified into three proficiency groups rated the stimuli, the scored data set was statistically analyzed in terms of the mixed effects model. It was confirmed that predictors such as pause length, pause position and utterance length significantly influence raters' evaluation scores. Especially, a dominating effect was found in such a way that raters gradually deducted scores in accordance with the increase of pause duration. In another experiment, a tree-based statistical learning technique was utilized to check which of the significant predictors played a more influential role than others. The findings in this paper are expected to be practically informative for both the test takers who are preparing for an English speaking test and the raters who desire to develop more objective rubric of speaking evaluation.

• Journal of Korean Society of Forest Science
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• v.96 no.2
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• pp.160-169
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• 2007

The data used to develop distance-independent individual models for natural mixed forests were collected from 712 remeasured permanent sample plots (25,526 trees) of 10-year periodic from 1990 to 2000 in Baihe Forest Bureau of Changbai Mountains, northeast China. Based on analyzing relationship between diameter increment of individual trees with tree size, competitive status, and site condition, the diameter growth models for individual trees of 15 species growing in mixed-species uneven-aged forest stands, that have simple form, good predicting precision, and easily applicable, were developed using stepwise regression method. The main variables influencing on diameter increment of individual trees were tree size and competition, however, the site conditions were not significantly related with diameter increment. The tree size variables (lnDBH and $DBH^2$) were the most significant and important predictors of diameter growth existing in all 15 growth models. The diameter increment was directly proportional to tree diameter for each species. For the competitive factors in growth model, the relative diameter (RD), canopy closure (P), and the ratio of diameter of subject tree with maximum diameter (DDM) were contributed to the diameter increment at a certain extent. Other measures of stand density, such as basal area of stand (G) and stand density index (SDI), were not significantly influenced on diameter increment. Site factors, such as site index, slope and aspect were not important to diameter increment and excluded in the final models. The total variance explained by the final models of squared diameter increment ($R^2$) for all 15 species ranged from 35% to 72% and these results compared quit closely with those of Wykoff (1990) for mixed conifer stands. Using independent data set, validation measures were evaluated for predicting models of diameter increment developed in this study. The result indicated that the estimated precision was all greater than 94% and the models were suitable to describe diameter increment.

• The Journal of the Acoustical Society of Korea
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• v.18 no.7
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• pp.17-22
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• 1999

In this paper we propose a new mixed method of LDA and tri-tone model to predict Korean prosodic break indices(PBI) for a given utterance. PBI can be used as an important cue of syntactic discontinuity in continuous speech recognition(CSR). The model consists of three steps. At the first step, PBI was predicted with the information of syllable and pause duration through the linear discriminant analysis (LDA) method. At the second step, syllable tone information was used to estimate PBI. In this step we used vector quantization (VQ) for coding the syllable tones and PBI is estimated by tri-tone model. In the last step, two PBI predictors were integrated by a weight factor. The proposed method was tested on 200 literal style spoken sentences. The experimental results showed 72% accuracy.