Dummy Regression Research Articles

정성변수를 고려한 공공아파트 기획단계 공사비 예측모델

공공아파트 프로젝트의 기획단계에서 수행되는 적정 공사비 예측은 기획부터 유지관리까지 전(全) 단계에 걸쳐서 영향을 미치게 되므로 명확한 예측기준 및 방법이 제시되어야 한다. 그러나 현재까지 다양한 다중회귀모델을 활용한 공사비 예측 방법이 개발되어 왔으나, 정성변수를 포함하여 공사비를 예측하는 방법에 대한 연구는 부족한 상황이다. 따라서 본 연구에서는 기획단계 활용을 위한 정성변수를 포함하는 공사비 예측모델을 개발하고자 하였다. 이를 위하여 공사비 영향요인을 분석 및 추출하고, 회귀분석을 위한 독립변수를 선정하였다. 그리고 정성변수를 포함하는 공사비 예측모델을 개발하며 사례적용을 통한 검증을 실시하였다. 개발된 공사비 예측모델과 "RESAMPLING 기법"을 사용하여 구조형식별 공사비 가산비율을 제시하였다. 본 연구에서 제시한 더미회귀모델과 가산비율을 활용하면, 일반적인 공사비 예측과 함께 동일한 평형, 세대수, 연면적에서 평면형식과 구조형식을 변경시켰을 때의 공사비 예측이 가능할 것으로 기대된다. In planning phase of Public Multi-Housing Projects, it is required to develop the methodology and criteria for fair cost prediction with influencing power from planning phase to occupancy phase. Many studies still have focused on the prediction of cost by multiple regression. However, there is no logical explanation about the influence of nonmetric variables for the prediction of cost in planning phase. Accordingly, this research pursues a cost prediction model including nonmetric variables for use in planning phase. There are 3 steps of this research : 1) Finding the factors influencing construction cost and assigning variables for a multiple regression. 2) Conducting a dummy regression analysis with nonmetric variables and model validation by comparing actual cost data. 3) Developing the ratio of RC structure cost to wall structure cost by using cost predection model. The results could establish cost prediction process including the influence of nonmetric variables and the ratio of RC structure cost to wall structure cost.

MEASURING THE STUDENTS’ PERCEPTION OF SERVICE QUALITY

Like in many other countries, higher education institutions in Indonesia are facing intense competition as the higher education market becomes globalized and competitive pressure intensifies. It is essential that higher education institutions continually monitor the quality of their services and commit themselves to continuous quality improvements in order to respond to the needs of their stakeholders. Measuring service quality in higher education is thus essential In order to provide a comprehensive view of the quality of education, it is valuable to assess not only student perceptions of their educational outcomes but also their perceptions of the manner in which polytechnic education is provided.This study aims at measuring the students’ perception of the service quality of education in a department; identifying differences of the student perception on the service quality based on their academic profiles; identifying which service attributes are more influential in providing service in higher education; and offering recommendation to the management which area(s) still need(s) some improvement.Using the 5-scale questionnaires, the researchers collected the data for the study from graduates of the 5 departments- Accounting, Marketing Management, Secretary Foreign Business Language and Taxation. Pearson Chi-Square and Alpha Cronbach techniques were used to test the validity and reliability before analyzing the data from the questionnaire. Descriptive statistics was deployed to find out the mean value of each indicator. This was followed bv Dummy Regression analysis. JThe findings of the study suggest that faculty plays the most prominent indicator in reflecting the students perception of service quality of department.

转型时期行业协会经济自治的影响因素分析——基于广东、浙江两地的经验数据

文章采用虚拟二分变量(binary dummy regression)方法，通过probit、logit和extreme value三种模型，对影响我国行业协会自治的因素进行回归分析。结果表明：理事单位占会员的比例、协会收入中来源于会费的比例越大，越不利于协会的自治；协会对违规者的惩罚力度、协会的决策程序民主度、政府授权给协会的管理权限越大(多)，协会的自治效果越好。其他因素如协会成立的时间长短、协会专职人员的数量多少、协会经费中用于会员支出的比例等均未发现显著影响。 This paper employs binary dummy regression, using probit, logit and extreme value to find out the influential factors associated with trade associations’ self-governance. The results show: The larger the tight-ness and the percentage of admission fees and fees from service to members and out-oriented service to trade associations’ total revenue is, the worse do trade associations self-govern; The more powerful the punishment and encouragement measures are, the more democratic the decision-making process is, the more autonomous rights government gives, the better do trade associations self-govern. Moreover, other factors such as the length of trade association’s history, the number of the association’s employers, the percentage of associa-tion’s expenditure for membership to its total expenditure have no significant effect. At last suggestion is given.

Using dummy regression to explore asymmetric effects in tourist satisfaction: A cautionary note

This research note addresses the misuse of standardized weights as measures of effect in dummy regression, which is the most frequently used technique for assessing asymmetric effects in the formation of tourist satisfaction. Unlike in regular regressions, standardized weights have no straightforward interpretation in dummy regressions, but they only carry the risk of providing misleading implications in theory building and guiding managerial action. To empirically underpin the arguments put forward in this note, an illustrative case example is used that provides insight into the underlying statistical mechanisms that cause unstandardized and standardized weights to provide significantly different implications in dummy regressions. The findings of this note should help to prevent bad practice in future studies that make use of the technique in assessments of asymmetric effects in customer satisfaction and/or the three-factor structure of customer satisfaction. However, the points put forward hold for dummy regressions in general.

Predictable patterns in ETFs' return and tracking error

PurposeThe purpose of this paper is to assess whether exchange‐traded funds (ETFs) can beat the market, as it is expressed by the Standard and Poor (S&P) 500 Index, examine the outperformance persistence, calculate tracking error, assess the tracking error persistence, investigate the factors that induce tracking error and assess whether there are predictable patterns in ETFs' performance.Design/methodology/approachThe author uses a sample of 50 iShares during the period 2002‐2007 and calculates the simple raw return, the Sharpe ratio and the Sortino ratio, regresses the performance differences between ETFs and market index, calculates tracking error as the standard deviation in return differences between ETFs and benchmarks, assesses tracking error's persistence in the same fashion used to assess the ETFs' outperformance persistence, examines the impact of expenses, risk and age on tracking error and applies dummy regression analysis to study whether the performance of ETFs is predictable.FindingsThe results reveal that the majority of the selected iShares beat the S&P 500 Index, both at the annual and the aggregate levels while the return superiority of ETFs strongly persists at the short‐term level. The tracking error of ETFs also persists at the short‐term level. The regression analysis on tracking error reveals that the expenses charged by ETFs along with the age and risk of ETFs are some of the factors that can explain the persistence in tracking error. Finally, the dummy regression analysis indicates that the performance of ETFs can be somehow predictable.Originality/valueThe findings of this paper may be of help to investors seeking investment choices that will help them to gain above market returns. In addition, tracking error‐concerned investors will be helped by the findings of the paper. Finally, the findings on return predictability can also be helpful to investors.

Oral health services utilization and influencing factors in downtown community residents older than 15 years in Beijing

To investigate the utilization of oral health services and to analyze the factors associated with oral health services for the community residents. Household health interview and oral health condition survey were conducted to obtain information about oral health services. The respondents were recruited by a multi-stage random cluster sampling procedure. Multiple dummy regression analyses were performed for the assessment of the relative effect of behavioural factors on dental attendance. A total of 2003 families, 4459 people participated in this study. The people seeking dental treatment accounted for 11.3% (502/4459) per year. Young people (OR = 2.072), having medical insurance system (OR = 2.835), short distance to see dentist (OR = 3.535), oral health awareness (OR = 2.595), poor self-assessment of oral health status (OR = 2.014) were the main factors which influenced dental attendance of community residents. The utilization of oral health service was low, particularly for middle-aged people and the elderly. Oral health education and medical insurance system should be strengthened.

Refining Kano's ‘quality attributes–satisfaction’ model: A moderated regression approach

Service and product quality is a multi-dimensional construct and not all quality attributes are viewed as equally important to customers. Several studies have applied the dummy variable regression method to recognize those product and service attributes that contribute more significantly to customer satisfaction. All attributes are classified into three quality factors (basic, performance, excitement) with each factor having different implications for customer satisfaction. This project proposes a moderated regression approach that corrects the flaws of the dummy regression method and produces more accurate attribute classification. The proposed method was validated using data collected from an online tax declaration service.

A hybrid decision model for the selection of capital equipment using AHP in conjoint analysis under fuzziness

Strategic level decision-making is very complex in nature because it consists of numerous variables and most of which cannot be quantified. These decisions are assisted based on the information available, which are both qualitative and quantitative. When comparing of different alternatives, the decision-maker should consider both the tangible and intangible benefits of different alternatives, i.e., fuzziness. The decision may be wrong if one considers only the tangible benefits of the alternatives. So, the intangible benefits should also be considered while making the decision. Generally, it is difficult to quantify these intangible benefits, because they are often fuzzy, complicated and subjective. So, there is a need of a methodology to evaluate both tangible and intangible benefits simultaneously. The conjoint analysis is applied to arrive at the relative weightage for the attributes and the part worth values for the levels using techniques like dummy regression, linear programming and to find an alternative method to arrive at the relative weightage and part worth values in conjoint analysis using analytic hierarchy process (AHP). Validation of the model was done through a real-time example.

From dummy regression to prior probabilities in PLS‐DA

AbstractDifferent published versions of partial least squares discriminant analysis (PLS‐DA) are shown as special cases of an approach exploiting prior probabilities in the estimated between groups covariance matrix used for calculation of loading weights. With prior probabilities included in the calculation of both PLS components and canonical variates, a complete strategy for extracting appropriate decision spaces with multicollinear data is obtained. This idea easily extends to weighted linear dummy regression so that the corresponding fitted values also span the canonical space. Two different choices of prior probabilities are applied with a real dataset to illustrate the effect for the obtained decision spaces. Copyright © 2007 John Wiley & Sons, Ltd.

The effects of inventory control and denied boarding on customer satisfaction: The case of capacity-based airline revenue management

This paper examines on the extent to which seat inventory control and denied boarding influence customer satisfaction. The effects of these core components of revenue management were analyzed within dummy regression models and ANOVAs. Our empirical analyses show that the effect of seat inventory control varies across booking classes. Reactions to cross-individual price differences caused by seat inventory control were more distinct in lower-priced booking classes. The same did not hold true for the impact of denied boarding on customer satisfaction, however, where there was no variation across booking classes. Furthermore, we found that favorable deviations from expected service performance (e.g. favorable cross-individual price differences) did not result in distinct satisfaction responses. Thus it must be assumed that revenue management practices have a net negative effect on customer satisfaction. Based on the results of the empirical analyses, implications for management and starting points for further research are presented.

A comparative study of linear and nonlinear models for aggregate retail sales forecasting

The purpose of this paper is to compare the accuracy of various linear and nonlinear models for forecasting aggregate retail sales. Because of the strong seasonal fluctuations observed in the retail sales, several traditional seasonal forecasting methods such as the time series approach and the regression approach with seasonal dummy variables and trigonometric functions are employed. The nonlinear versions of these methods are implemented via neural networks that are generalized nonlinear functional approximators. Issues of seasonal time series modeling such as deseasonalization are also investigated. Using multiple cross-validation samples, we find that the nonlinear models are able to outperform their linear counterparts in out-of-sample forecasting, and prior seasonal adjustment of the data can significantly improve forecasting performance of the neural network model. The overall best model is the neural network built on deseasonalized time series data. While seasonal dummy variables can be useful in developing effective regression models for predicting retail sales, the performance of dummy regression models may not be robust. Furthermore, trigonometric models are not useful in aggregate retail sales forecasting.

Visible and near Infrared Spectroscopy of Beef Longissimus Dorsi Muscle as a Means of Dicriminating between Pasture and Corn Silage Feeding Regimes

Near infrared (NIR) reflectance spectroscopy was used as a tool to classify beef muscle samples according to their feeding regime. Seventy-eight beef longissimus dorsi muscle samples both intact and minced were scanned in a NIRS 6500 instrument (NIRSystems, MD, USA) in reflectance. A dummy regression technique was developed to differentiate beef muscle samples, which originated from beef feed exclusively on pasture or/and mainly on corn silage feeding regimes. Ninety percent of the pasture-fed beef muscle samples were correctly classified using principal component regression (PCR) and 86% of beef fed on corn silage were correctly classified. Both muscle chemical composition and physical characteristics explained the classification results. The results in the present study showed the potential of muscle optical properties for classification and traceability of meat muscles in the food chain.

Identification of broiler chicken meat using a visible/near-infrared spectroscopic technique

A near-infrared spectroscopic method was developed with a dummy regression technique to differentiate meat originating from broilers and Chinese local chickens. Best classification accuracies of 100%, 92%, 96% and 92% were achieved for minced thigh meat, minced breast meat, breast cut without skin and breast cut with skin respectively. Comparison among the regression models of MLR, PCR, PLS and mPLS did not show obvious differences in classification accuracy. Scatter correction and derivative treatment of the spectral data before discriminant analysis often improved the classification accuracy for minced meat, while for meat cuts, spectra without pretreatment produced better classification. In general, using the full spectrum of 400–2500 nm produced satisfactory classification. The spectrum in the visible region of 400–750 nm, the short-wavelength NIR region of 750–1100 nm or the long-wavelength NIR region of 1100–2500 nm can also produce satisfactory classification depending on sample presentation methods and regression models. The spectroscopic classification was supported by physical and chemical properties of meat samples, which showed significant differences in collagen and fat contents and pH and chromatic values between the two groups of chickens. The results of the present study indicate that NIR spectroscopy can be used to identify broiler meat or carcass from those of local chickens. © 1999 Society of Chemical Industry

High School Factors That Influence Students to Remain in School

ABSTRACT This article describes part of a study to understand the ways in which school factors influence high school students to stay in school for the senior secondary non-compulsory years. A causal model was proposed in which student background characteristics and school factors had direct influence on students' intentions and also had less direct influence through two intervening variables, namely, student achievement level and student perceptions of the quality of school life. An important step in the study was establishing which schools were significantly different from each other (substantially and statistically) after controlling for student background characteristics. A series of regression analyses appropriate for the model was carried out with school membership represented by a set of dummy variables. Each dummy regression coefficient was then converted to a more easily interpreted statistic, namely, the deviation of the dependent variable at school level from its grand mean after controlling for other independent variables. The adjusted deviations identified groups of schools that were significantly different from each other. Quantitative and qualitative information about significantly different schools then indicated the parameters that should be more closely observed to understand the school factors producing the school differences.

Education and earnings in the Netherlands: an empirical analysis

In this paper three models which describe the relation between earnings and education are estimated, using one single data set. One model is a simple dummy regression model in which the educational variables are exogenous. Both other models take account of the fact that individuals choose their optimal amount of education, and is therefore endogenous. In all three models I try to specify the equations in the same way as others have done with other data sets. It turns out that in each model important conclusions reached in earlier research, are not supported by the empirical findings reported here.

Use of dental services among Danish youths: role of the social environment, the individual, and the delivery system.

The purpose of the present study was to analyze the separate effect and the total effect of the social environment, the individual and the delivery system on frequency of use of dental services among youths. The variables of use were divided into the three main groups according to Coleman (12). Information concerning use of dental services, individual and structural variables was obtained by a self-administered questionnaire to 756 Danes 20-21 yr old in 1984-85. Information concerning social environmental variables was obtained by a postal questionnaire to the mothers of the individuals in 1974 (16). Information from 552 mothers was available. Firstly, the variables concerning the social environment were inserted into a multiple dummy regression analysis as independent variables, and it was found that the following characteristics of the mothers were significant predictors: regularity of dental visits and perceived economic barriers. Secondly, the variables concerning the individual resources were set into a multiple dummy regression model as independent variables. The results showed that the following variables had a significant effect: sex, social conditions, pain tolerance, dental anxiety, and perceived economic barriers. Thirdly, multiple dummy regression analysis showed that among the structural variables general assessment of Child Dental Care compared to Youth Dental Care, and a personality assessment of the general dental practitioner were significant predictors. Finally the predictors from the three main groups all together were inserted as independent dummy variables into a regression model. The results showed that sex, social conditions, pain tolerance, dental anxiety, perceived economic barriers of the youth themselves, general assessment of Child Dental Care compared to Youth Dental Care were significant predictors.(ABSTRACT TRUNCATED AT 250 WORDS)

Tenure Choice in the Dutch Housing Market

In this paper, tenure choice in complex housing markets is examined, that is, in markets with more than a simple choice between own and rent. The paper has both substantive and technical foci. The substantive focus is to extend the authors' research on the links between housing and mobility and to provide detailed information on the way in which dwelling choices are made after the decision to relocate. The technical focus is to continue the authors' concern with building robust models of urban processes. The technical concerns are focused on special forms of automatic interaction detection and dummy variable multiple regression to estimate the influence of household characteristics and previous housing situation on dwelling choice. The data used in the analysis are part of a large sample taken in 1981 of all Dutch households. The automatic interaction detection method is used as a form of exploratory data analysis to identify the underlying ‘structure’ in the data. The results are used as input to the dummy regression process, which, in combination with the proportional reduction in uncertainty measures, establishes the importance of income and the role of regional variations, age, and type of house as major predictors of tenure choice. A main conclusion from the research is that, even though income is the most important predictor, age, size of family, type of house, and price also affect tenure choice. Even more important is the conclusion that it is essential to do separate analyses for separate tenures.

Collective Bargaining and Faculty Compensation: A Comparative Analysis

Multiple regression is used to estimate faculty compensation levels and compensation change for 46 paired union and nonunion institutions of higher education for the year 1974-75. With the five other independent variables controlled, the union/nonunion dummy regression coefficient accounts for over $1,000 more in average annual compensation levels for unionized faculties than for their nonunion counterparts. In addition, the union/nonunion variable is the most important single explanatory factor in the analysis of compensation change from 1969-70 to 197475.