Earticle

The purpose of this study is to find out the spatial characteristics of residential environment that is suitable for raising children, by analyzing the effect of the characteristics of the residential environment in the apartments on the children residential ratio. For the analysis, we constructed variables, based on the census data for apartment complexes in Seoul and Gyeonggi-do and conducted a multivariate regression analysis based on microscopic spatial units called ‘National Basic Zone.’ From the results of the analysis, the following characteristics of residential environments with a high children residential ratio were derived. First, Childcare households tend to reside more in new apartments in large-scale complexes, even if the cost is higher to a certain extent. Second, the child residential ratio is higher in the complexes which have more parking spaces and the ratio of underground parking is higher. Third, Childcare households do not prefer housing units smaller than 40㎡. Fourth, Childcare households consider accessibility to educational facilities more important than the distance to major transportation hubs or job centers.

본 연구는 중소기업의 자금조달 방식 다양화와 금융접근성 개선의 일환으로 도입된 기술력 평가모형의 ‘미래 진보성’을 확인하고자 시작되었다. 기술금융기업의 경영성과(성장성, 수익성, 안정성)를 종속변수로, 기술력 평가항목을 독립변수로, 기업규모 및 산업특성과 관련된 종업원 수, 업력, 자산규모, 표준산업 분류를 통제변수로 설정하여 다변량 회귀분석을 실시하였다. 분석결과 기술력 평가항목은 기업의 수익성을 유의하게 설명하지 못하며 성장성에 대해 제한적인 설명력을 지니고 있는 반면, 안정성과 관련해서는 기술개발역량 항목이 기술금융기업의 부채비율을 유의하게 설명하는 변수임을 확인하였다. 따라서 향후 기술력 평가모형의 조정 및 투자용 기술력 평가모형 개발 시 기업의 성장성과 수익성에 대한 ‘미래 진보성’의 반영 강화가 필요하다는 결론을 도출하였다.

This study started to identify the “Forward-looking” of the technology appraisal model introduced to diversify financing methods of SMEs and improve financial accessibility. The multivariate regression analysis was performed by setting the business performance(growth, profitability, and stability) of technology financing companies as dependent variables, technology appraisal items as independent variables, number of employees, age of the company, asset and the Korea Standard of Industry Classification related to firm size and industry characteristics as control variables. As a result of the analysis, the technology appraisal items did not explain the profitability of the company significantly and had a limited explanatory power on growth potential. However, in terms of stability, we confirmed that R&D capacity is a significant variable explaining the debt ratio of technology financing companies. Therefore, it is concluded that the 'Forward-looking' reflection on the growth and profitability of the company should be strengthened in the future adjustment of the technology appraisal model and the development of the technology appraisal model for investment.

본 연구는 고령화연구패널(KLoSA) 1차(2006년)∼6차(2016년) 자료를 이용하여 은퇴가 삶의 만족도에 미치는 영향을 다변량 다중회귀 분석(Multivariate Multiple Regression Analysis)을 이용하여 추정하였다. 우리나라 대표 표본을 가지고 국내에서 삶의 만족도에 대한 다변량 다중회귀분석을 수행하여 은퇴와 삶의 만족도에대한 분석의 정확성을 향상시키고자 하였다. 분석결과는 다음과 같다. 첫째, 은퇴는 고령자의 삶의 만족을 감소시키는 결정적인 요인이다. 특히 본 연구는 패널데이터를 분석하여 영역별 만족도의 감소를 확인할 수 있었는데은퇴이후 만족도가 가장 많이 하락하는 영역은 건강상태에 대한 만족도로 은퇴이후 약 14%의 감소를 보였으며다음은 자녀와의 관계(약 10% 감소), 배우자와의 관계(약 9% 감소), 전반적인 삶의 질에 대한 만족도(약 8% 감소)의 순으로 감소되는 것으로 나타났다. 둘째, 은퇴시기가 늦을수록, 고용상태를 유지하는 기간이 길수록 삶의 만족도는 높아진다. 이는 노동시장에서 더 오래 남아 근로를 했던 고령자의 삶의 만족이 높은 것으로, 은퇴이전 더 오랜 기간 노후준비를 할수록 은퇴이후 삶의 만족이 증진된다는 것을 시사한다. 셋째, 인구․사회적 특성에 따라 삶의 만족에 있어서 5가지 하위 요인들에 미치는 효과는 다르게 나타났다. 남자의 경우 배우자와의 관계에 대한 만족도가 증진되었고, 가구총소득이 높은 계층은 가구총소득이 낮은 계층에 비해 경제상태 만족도가 높았다. 또한, 배우자의 고용상태가 취업자일 경우 배우자와의 관계에 대한 만족도가 높았으며, 자발적 은퇴는 비자발적 은퇴에 비해 경제상태 만족도, 배우자와의 관계에 대한 만족도가 높았다. 넷째, 건강상태가 좋을수록 학력이 높아질수록 삶의 만족도는 증진되는 효과가 나타났고, 직업상태는 상용직에 비해 임시직/일용직의 삶의 만족도가 감소하였다. 자영업자는 상용직에 비해 경제상태 만족도가 줄어들었다. 본 연구는 5가지 영역별 삶의 만족도에 미치는 효과를 분석함으로써 은퇴 이후 노후준비를 위한 사회․제도적 지원과 방안을 다음과 같이 제시하였다. 첫째, 신체적 노후준비, 경제적 노후준비, 가족 간 정서 및 사회적 노후준비가 함께 이루어졌을 때 전반적인 삶의 만족도에 미치는 효과가 더 커질 수 있다고 판단되며, 둘째, 노동시장에서의 은퇴가 국가 및 기업차원의구조적인 측면에서 이루어지기 보다는 개인의 생산성 저하 및 판단에 의해 자발적인 측면에서 이루어질 수 있는노동환경이 개선되어야 한다고 생각된다.

This study explored the relationship between retirement and life satisfaction using Korean Longitudinal Study of Ageing(KLoSA) wave 1(2006) to wave 6(2016) data. The dependent variable of life satisfaction in this study was consisted with five dimensions of life satisfaction (satisfactions on one’s health, economic status, relationship with spouse, relationship with children, and overall life condition) as such multivariate multiple regression analyses was utilized due to the inter-relationships among the dependent variables. From the analyses from a total of 1,149(total of 2,298 observations) balanced panel showed that retirement was the major factor that influencing life satisfaction; after retirement individuals satisfactions on their own health, relationship with their spouse, relationship with their children and overall life condition were decreased. In addition, the time of retirement also influenced life satisfaction; those who stayed in workforce longer had higher levels of life satisfaction. Individuals’ background characteristics influenced each dimension of life satisfaction in different ways; men compared to women had higher levels of relationship satisfaction with spouse, those who had higher levels of household income showed higher levels of economic satisfaction. People who retired voluntarily showed higher levels of economic satisfaction and spouse relationship satisfaction. People who had higher levels of health condition and education showed higher levels of satisfaction with overall life condition. Those who work full-time had higher levels of life satisfaction compared to other working type. Based on these findings, it was suggested that when preparing for retirement all aspects of life such as health, relationship, and social condition in addition to economic and financial readiness should be considered. Retirement should be treated as individual decision making issue rather than systematic corporate issue in workforce. Future research on examining life satisfaction changes after retirement is recommended.

Purpose: This study aimed to identify factors influencing professional quality of life (ProQOL) of emergency department (ED) nurses. Methods: A total of 213 ED nurses from regional emergency medical centers and institutions in Busan, Ulsan, and Gyeongnam participated in an online survey between June 12 and September 10, 2024. Validated tools were used to collect data on demographic and job-retated characteristics, nursing work environments, workplace incivility, job embeddedness, and ProQOL. Analyses included descriptive statistics, MANOVA, and multivariate multiple regression using SPSS 29.0. Results: MANOVA revealed significant multivariate effects of age, ED work experience, Satisfaction to ED, and type of ED across three ProQOL subdomains, with Pillai's Trace ranging from .07~.48 (all p<.05). Multivariate regression revealed that job embeddedness increased compassion satisfaction (B=0.39, p<.001) and reduced burnout (B=-0.23, p<.001). Incivility from coworkers and patients/families increased burnout (B=0.09, p<.001) and secondary traumatic stress (B=0.19, p<.001). Department dissatisfaction consistently worsened all ProQOL outcomes (B=-3.83~0.36, all p<.05), while age under 30 predicted lower compassion satisfaction (B=-1.64, p=.014) and higher secondary traumatic stress (B=-2.68, p=.005). Conclusion: Incivility, job embeddedness, and department satisfaction were key predictors of the ProQOL of ED nurses. Organizational efforts that implement clear anti-incivility policies, strengthen peer support and teamwork, and enhance job embeddedness through mentorship and recognition systems are essential to improving the ProQOL of ED nurses.

최근 상업용 통계 패키지의 발달에 힘입어 다변인 통계분석에 기초한 연구들이 양산되고 있다. 다변인 분석은 단변인 통계에 비해 복잡한 연구문제를 탐색할 수 있는 장점이 있지만, 통계분석의 복잡성으로 인하여 절차상 오류들이 더러 발견된다. 더욱이, 다변인 통계분석의 수학적 기초가 복잡하여 그 원리를 이해하기 어렵고, 분석방법 및 결과 해석이 난해할 수 있으며, 다양한 분석법들이 상반된 결과를 낳아서 결과해석이 곤란해질 수 있다. 따라서 본 연구에서는 다변인분석 적용상의 가능한 오류와 주의점들을 기술하여 이러한 오용을 줄일 수 있는 방안을 제시하고자 하였다.

Due to the recent developments in commercial statistical packages, vast amount of research articles based on multivariate statistics have been published. While the multivariate statistics have advantages over the univariate statistics in dealing with more complicated research hypothesis, abuses and misuses in it's application have been frequently noticed in many researches, due to the underlying complexities. Specifically, it is difficult to understand the basic principle due to the mathematical complexities underlying in it, henceforth making the interpretation of the analysis result be difficult. Even worse, different choice of the analysis methods sometimes result in contradicting results, making the interpretation implausible. This study tried to examine the cases of misuses in the application of multivariate statistics, and to identify the problems. Finally, several precautions for reducing the incidents was proposed.

본 연구의 목적은 메타분석을 통하여 지역아동센터 이용 아동의 자아존중감 향상 프로그램의 효과성에 관한 특징을 규명하는 데 있다. 연구대상은 2018년 6월 현재까지 검색된 39편의 지역아동센터의 자아존중감 관련 프로그램 평가논문이며, 분석에 포함된 변수는 조사평가, 프로그램 구성 및 프로그램 개발 활동 영역의 9개 변수이다. 통계분석은 CMA (Comprehensive Meta-Analysis) 3.0을 사용하여 메타아노바와 설명적 메타분석으로서 단일변량 및 다중변량 메타회귀분석을 적용하여 분석하였다, 분석 결과, 지역아동센터의 자아존중감 향상 프로그램의 평균 효과크기는 .942로 나타났다. 효과크기의 이질성에 대한 메타아노바 분석 결과, 총 회기 11~20회, 1회기 당 50분~60분, 프로그램 참여자 10인 이하, 자아존중감 단일목표, 프로그램 개발 활동과 관련된 프로그램이론 및 프로그램 개발과정 정도가 높은 경우에 효과크기가 가장 높게 나타났다. 효과크기 이질성의 인과성에 대한 단일변량 및 다중변량 메타회귀분석 결과, 프로그램 목표 수, 프로그램 참여자 수, 프로그램 이론, 프로그램 개발과정의 정도가 통계적으로 유의미하며, 프로그램 목표가 자아존중감 단일목표일수록, 프로그램 참여자 수가 적을수록, 그리고 프로그램 개발이론과 프로그램 개발과정 정도가 높을수록 효과크기가 커지는 것으로 나타났다. 자아존중감 효과크기의 예측모형에서는 4개 변수 중에서 프로그램 개발과정 정도가 모형변화량에서 가장 큰 것으로 나타났다. 끝으로 메타분석 연구결과의 내용에 대한 학문적인 논의와 지역아동센터에서의 자아존중감 향상 프로그램 및 설명적 메타분석을 위한 제언을 하였다.

The purpose of the study is to identify the characteristics of the effectiveness of self-esteem improvement programs for the children using Community Children Centers through meta-analysis. The research subject was 39 evaluation papers on self-esteem program in Community Children Center searched in June 2018. The variables included in the analysis were 9 variables in the areas of survey assessment, program composition and program development activities. Statistical analysis was conducted by the meta-anova, univariate meta-regression and mutivaratiate meta-regression analysis using CMA(Comprehensive Meta-Analysis) 3.0. The analysis results are as follows. The average effect size of the self-esteem improvement program at the Community Children Center is .942. Analysis of meta-anova for heterogeneity of effect size showed high effect size in pretest-posttest control group design, 11 to 20 sessions, 50 to 60 minutes per session, 10 participants or less, high degree of program theory and program development process. Univariate and multivatate meta-regression analysis of the causality of effect size heterogeneity showed that the number of program goal, number of participant, level of program theory and program development activity were statistically significant; the fewer program participants, the fewer program goals, the higher the program theory and program development process, the greater the effect. The program development process is the most important variate for the incremental change in the predictive model analysis. The academic meanings of the study results was discussed, and the future directions of practices and explanatory meta-analysis was suggested.

The gender gap in the attitudes toward the use of violence is one of the heavily scrutinized research topics in political science. The claim that women are more peace loving and politically liberal than men is known as the women and peace hypothesis in the study of international relations. One of the most cited theoretical roots of the women and peace hypothesis is the ‘maternal thinking’ argument. According to the ‘maternal thinking’ argument, women’s politically liberal and peace loving attitude is the political representation of women’s child caring experience. In this paper, using multivariate linear regression analyses on the 109th U.S. Congress voting records, I test ‘maternal thinking’ argument and propose an alternative explanation on women's liberal political attitude. I argue that the biological difference between men and women is not a sufficient explanatory variable in explaining women’s political attitude. In fact, it is individual’s political ideology that influences one’s political attitude.

The influence of observations on the Wilks' lambda test of a linear hypothesis in multivariate regression is investigated using the local influence method. The perturbation scheme of case-weights is considered. A numerical example is given to show the effectiveness of the local influence method in identifying the influential observations.

This study estimates the possibilities of hotel bankruptcy using various analytic methods such as multivariate discriminant model, logistic regression model and artificial neural network model. The estimated models suggest that debt-burned hotels with low profit margin and return on common stockholders’ equity are more likely to be candidates of bankruptcy. The analysis of in-model variables, along with a cross-group comparison of financial ratios, suggests that bankrupt hotels have heavily relied on debt to finance fast sales growth without paying proper attention to controlling their operating expenses and financing costs. Author suggests in conclusion that to avoid bankruptcy risk hoteliers are encouraged to adopt a prudent growth strategy accompanied by less debt financing and tighter cost control.

상품에 대한 고객들의 구매네트워크는 고객 간의 커뮤니케이션 네트워크를 기반으로 하여 존재한다. 본 연구에서는 커뮤니케이션 네트워크와 구매네트 간의 상호의존성과 관련하여, 커뮤니케이션 네트워크 상 고객의 내향중앙성과 외향중앙성이 다른 고객으로 하여금 특정 상품을 선택, 구매함에 있어서 얼마나 영향을 주는지 그리고 어떠한 형태로 영향을 주는지를 비모수적인 방법인 다변량 적응회귀스플라인모형(MARS)을 사용하여 실증적으로 검토하였다. MARS모형의 추정결과, 내향중앙성과 외향중앙성 모두 상품의 선택확률에 유의적인 영향을 비선형적으로 준다는 것, 선택확률에 대한 내향중앙성과 외향중앙성의 효과가 위로 볼록하다는 것, 그리고 선택확률을 최대화시키는 내향중앙성과 외향중앙성의 최적 조합이 존재한다는 것을 발견하였다.

One of the most important research questions in social network analysis is to capture, or predict, differences in tie strengths across node pairs. In a majority of marketing-based networks, multiple relations between nodes are not independent from one another. For example, aside from their core communication services, mobile phone service providers provide their customers with various extra products or services, such as mobile phone games, MP3 songs, and e-books. Since these extra products or services may proliferate via communication network among mobile phone users, it is critical to understand interwoven structures between communication and purchase networks. A growing body of studies in marketing has applied sociogram-based concepts and methods to investigate various issues of interrelationships among customers. None of these extant studies, has, thus far, examined interdependencies between communication relations and purchase relations. This paper aims to empirically investigate possible interdependencies between communication network and purchase networks. To this end, we measured indegree and outdegree centralities for each node in communication network and then rigorously investigated possible effects of the two centrality indices in communication network on their relations in purchase network on the basis of multivariate adaptive regression spline (MARS). In particular, degree centralities were measured for each pair of nodes in the communication network, as follows:where denotes connected (1) or disconnected (0) directed ties starting node and ending at node . Let denotes a binary observation for whether node made purchases (1) for a given product or service. Then, MARS model was fitted to data across all the possible pairs of nodes, as follows:where denotes probability of node making purchases for the product or service, is an unknown target function to be estimated, represents candidate explanatory variables for the directed tie , is the total number of hyperplanes, denotes the -th base spline function, and is the spline coefficient associated with . MARS model was fitted to real mobile phone usage data containing information about two particular types of relations among nodes: communications (i.e. phone call records) and purchases for a non-free extra service. Major findings attained from this particular application can be summarized as follows: First, both indegree and outdegree centralities were found to increase choice probabilities for the non-free extra service. Mobile phone users who might have relatively high scores for indegree and outdegree centralities would, therefore, exhibit relatively large influence on purchase decisions of those who were communicationally connected to them. Second, choice probability responses functions of indegree and outdegree centralities were not linear but nonlinear. These nonlinearities have been found by none of all the extant studies in the marketing literature, primarily because all of them have imposed linearity presumptions a priori on the effects of centralities on adoptions of information and/or products. Third, response surface of choice probabilities were not monotonically increasing but concave. Choice probabilities for the non-free extra service were, therefore, maximed at particular combinations of indegree and outdegree centrallities, rather than at maximum values of each of them. This last finding has not been reported by any of the extant studies in the marketing literature, mainly because they have failed in accounting for decisive possibilities that indegree and outdegree centralities might affect choice probabilities nonlinearly even with higher-order interaction effects.

세계경제의 침체가 장기화되면서 수출에 의존하는우리나라 경기는 매우 어려운 상황에 직면해 있다. 수출이 중심인 우리나라 경기구조에서 수출 부진은 기업의 수익성 저하로 이어진다. 수익성 저하는 기업의부실로 이어지며 기업부실은 우리나라 경제 전반에많은 문제를 발생시킨다. 따라서 본 연구에서는 코스닥기업의 방송통신 및 정보서비스업, 제조업, 유통업분야의 재무변수를 이용하여 기업부실예측모형을 제시하였다. 이를 위하여 사용된 재무변수는 유동성지표, 레버리지지표, 수익성지표를 사용하였다. 분석방법으로는 다중인자분석을 실시하여 재무변수의 공통요인을 추정하였고, 추정된 재무변수를 이용하여 로지스틱회귀함수와 다변량 선형판별함수의 판별력을 비교하였다. 다중인자모형에서 인자적재행렬의 추정은 주성분방법을 사용하였고, 직교회전 방법인 베리맥스 회전으로 재무변수의 구조를 단순화시켜 복잡한 특징을해석하였다. 로지스틱회귀모형에서는 최우추정방법으로 회귀계수를 추정하였고, 모든 변수를 포함한 모형이 적합한 모형임을 확인하였으며 절편을 제외한 모형의 유의성 검정을 통하여 회귀계수의 적합함을 확인하였다. 다변량 판별분석모형에서는 두 집단의 공분산행렬이 서로 다르게 나타났으나 선형함수와 이차함수의 오분류율을 비교하여 정규분포를 가정한 선형판별함수를 선택하였다. 그리고 정분류율을 계산한 결과두 모형의 판별력은 로지스틱회귀모형이 더 좋은 것으로 나타났다. 그러므로 로지스틱회귀모형의 예측정확도를 나타내는 ROC곡선과 통계량을 제시하였다.

As the downturn in the global economy is prolonged, South Korean business conditions depending on the export is faced with a very difficult situation. The slump in exports in the country's economic structure leads to a deterioration of profitability, which leads to the degradation of companies, and the insolvent companies eventually generate a lot of problems throughout our economy. Accordingly this study suggests a corporate insolvency prediction model using financial variables of companies in broadcast communications, information services, manufacturing, and retail sectors in KOSDAQ. Financial variables used were fluidity indices, leverage indicators, and profitability indicators. As analysis method, the common cause of financial variables was estimated by conducting a multi-factor analysis, and the discrimination power in the logistic regression function and the multivariate linear discriminant function was compared respectively. We used the principal component method for the estimation of factor loading matrix in the multi-factor model, and analyzed complex features by simplifying the structure of the financial variables using the Varimax rotation method which is an orthogonal rotation method. We estimated the regression coefficients by maximum likelihood estimation method in logistic regression models, verified them through the significance test of the model without an intercept, and found that the model with all variables was appropriate. In multivariate discriminant analysis model, covariance matrix between the two groups were differently resulted, but we selected linear discriminant function with the assumption of a normal distribution by comparing the misclassification rate of the of the linear function and the quadratic function. It was found that the discrimination power of logistic regression model was superior between the two models based on the rate of classified information. Finally we suggested the ROC curves and statistics presenting the predictive accuracy of the logistic regression model.

본 연구에서는 UV-VIS spectrophotometer를 이용한 total carotenoids, flavonoids, phenolics 함량 데이터와 FT-IR 스펙트럼 데이터를 다변량통계분석법을 통하여 기능성 성분 함량이 높은 아프리칸 얌 고속 선발 시스템을 구축하였다. 62개 아프리칸 얌의 total carotenoids 함량은 $0.01-0.91{\mu}g{\cdot}g^{-1}$ dry wt 나타냈다. Total flavonoids와 phenolics 함량은 $12.9-229.0{\mu}g{\cdot}g^{-1}$ dry wt와 $0.29-5.2mg{\cdot}g^{-1}$ dry wt로 각각 나타났다. 아프리칸 얌은 FT-IR 스펙트럼상의 1700-1500, 1500-1300, $1,100-950cm^{-1}$, 부위에서 중요한 스펙트럼 변화가 나타났다. 이 부위는 각각 amide I과 II을 포함하는 아미노산 및 단백질계열의 화합물, phosphodiester group을 포함한 핵산 및 인지질 그리고 단당류나 복합 다당류를 포함하는 carbohydrates 계열의 화합물들의 질적, 양적 정보를 반영하는 부위이다. PCA 분석과 PLS-DA 분석에서 62개 아프리칸 얌은 유연성이 높은 종으로 3개의 그룹을 형성하였다. 아프리칸 얌의 FT-IR 스펙트럼 데이터와 UV-VIS spectrophotometer을 이용한 total carotenoids, flavonoids, phenolics 함량 데이터 간에 PLS regression 분석하였다. Total carotenoids, flavonoids, phenolics 함량 성분의 실측 값과 예측 값간에 상관계수($R^2$)가 각각 0.83, 0.86, 0.72로 나타났다. 이 결과, 아프리칸 얌으로부터 FT-IR 스펙트럼을 이용한 total carotenoids, flavonoids, phenolics 함량 예측이 가능하였다. 본 연구에서 확립된 대사체 수준에서 아프리칸 얌의 유용 기능성 성분 함량 예측 모델링을 통해 품종, 계통의 신속한 선발 수단으로 활용이 가능할 것으로 예상된다.

We established a high throughput screening system of African yam tuber lines which contain high contents of total carotenoids, flavonoids, and phenolic compounds using ultraviolet-visible (UV-VIS) spectroscopy and Fourier transform infrared (FT-IR) spectroscopy in combination with multivariate analysis. The total carotenoids contents from 62 African yam tubers varied from 0.01 to $0.91{\mu}g{\cdot}g^{-1}$ dry weight (wt). The total flavonoids and phenolic compounds also varied from 12.9 to $229{\mu}g{\cdot}g^{-1}$ and from 0.29 to $5.2mg{\cdot}g^{-1}$dry wt. FT-IR spectra confirmed typical spectral differences between the frequency regions of 1,700-1,500, 1,500-1,300 and $1,100-950cm^{-1}$, respectively. These spectral regions were reflecting the quantitative and qualitative variations of amide I, II from amino acids and proteins ($1,700-1,500cm^{-1}$), phosphodiester groups from nucleic acid and phospholipid ($1,500-1,300cm^{-1}$) and carbohydrate compounds ($1,100-950cm^{-1}$). Principal component analysis (PCA) and subsequent partial least square-discriminant analysis (PLS-DA) were able to discriminate the 62 African yam tuber lines into three separate clusters corresponding to their taxonomic relationship. The quantitative prediction modeling of total carotenoids, flavonoids, and phenolic compounds from African yam tuber lines were established using partial least square regression algorithm from FT-IR spectra. The regression coefficients ($R^2$) between predicted values and estimated values of total carotenoids, flavonoids and phenolic compounds were 0.83, 0.86, and 0.72, respectively. These results showed that quantitative predictions of total carotenoids, flavonoids, and phenolic compounds were possible from FT-IR spectra of African yam tuber lines with higher accuracy. Therefore we suggested that quantitative prediction system established in this study could be applied as a rapid selection tool for high yielding African yam lines.