The purpose of this study was to identify the behavioral, attitudinal, and demographic correlates of light, medium, and heavy users of eating out at family restaurants. Among 358 reponses from the subjects, 224 responses were utilized for the analysis, and 134 responses were reserved for validating the discriminant function. Descriptive statistics, reliability analysis, stepwise discriminant analysis, canonical discriminant analysis, and anova analysis were used for this study. The findings from this study were as follows: First, He behavioral characteristics were found to discriminate among the three usage groups. Second, it was found that heavy users expressed greater difference between perception and expectation on the quantity of food that are appropriately served and the consistent quality of food at every visit. Third, the usage rate of eating out was not dependent on the sex, but dependent on the companion, average expenditure, and the time of eating out in chi-square test. Finally, the results of the study provide some insight into the pattern of marketing strategies that can be successfully used by the managers of family restaurants.
The purpose of this study was to describe perimenstrual symptom severity levels and perimenstrual distress patterns of women. The study performed the discriminant analysis in which included seven factors : age, pariety, social support, menstrual socialization(mother's symptom, sister's symptom, and menstrual effect), attitude of sex role and depression. The subjects were 283 women that they were not pregnant or lactating, had at least one period in past three months, would understand the purpose of study and willingly accepted the participation. The data analysis was done by pc-SAS program after data collection from Nov. 20, 1997 to Dec. 18, 1997. The descriptive analysis was done to explore general characteristics of the subjects and the stepwise discriminant analysis was done to verify factors in relation to perimenstrual symptom severity levels(severe vs mild menstrual symptom group) and perimenstrual distress patterns(spasmodic vs congestive menstrual symptom group). The instruments were selected for this study from Interpersonal Support Evaluation List(ISEL) by Cohen and Hoberman(1983), Center for Epidemic Studies Depression(CES-D) by Radloff(1977), and Sex Role Attitude Scale by Yunok Suh(1995), Mother's symptom and sister's symptom measurements by Woods, Mitchell & Lentz(1995), and menstrual effect by Brooks-Gun & Ruble(1980). The major findings of this study are as follows : 1. Of the 283 women, 93 women(32.9%) were assessed to severe perimenstrual symptom group and 190 women(67.1%) were assessed to mild perimenstrual symptom group. Results from the stepwise discriminant analysis showed three factors, such as depression, menstrual effect, and age, significantly related to perimenstrual symptom severity and they explained 20% of the total variance. The linear discriminant equation included three factors related to perimenstrual symptom groups was showed(Z=1.445 depression+0.174 menstrual effect-0.054 age). The cutting score(Z) was 2.809. We classified the severe perimenstrual symptom group by more than the cutting score 2.809 and the mild perimenstrual symptom by less or equal than the cutting score 2.809. The correctedness of posterior probability from discriminant equation was 72% as two perimenstrual symptom group classifications. 2. Of the 264 women, 139 women(52.7%) were assessed to spasmodic perimenstrual distress group and women(47.3%) were assessed to congestive perimenstrual distress group. Results from the stepwise discriminant analysis showed two factors, such as depression, age, significantly related to perimenstrual distress groups and they explained 8% of the total variance. The linear discriminant equation included two factors related to perimenstrual distress group was showed(Z=-0.084 age-0.776 depression). The cutting score(Z) was -3.759. We classified the spasmodic perimenstrual distress group by more than cutting score -3.759 and the congestive perimenstrual distress group by less or equal than cutting score -3.759. The correctedness of posterior probability from discriminant equation was 65% as two perimenstrual distress group classifications.
This study classified figure types of adult males into several kinds of shape to provide fundamental data for their clothing sizing system. The subjects were 1496 men aged between 20 and 60 years old. Data were analyzed by factor analysis, cluster analysis and discriminant analysis. The results were as follows 1. For the result of the interview, the data were grouped into three age brackets: 20-35,31-45 and 41-60 years. 2. Factor analysis using values, which were measurements divided by either weight or height, was carried out to extract factors which characterize the various figures. fve factors to determine the figure types were extracted. 3. Cluster analysis using factor scores was carried out to categorize the figure types within the age groups. Figure types, describing shoulder angie and body shape, were categorized into 3 per age group. 4. Stepwise discriminant analysis w3s used to ensure that these clusters could be utilized with appropriate hit ratio. The hit ratio for each age group was around 80%.
Journal of the Korean Society of Clothing and Textiles
/
v.26
no.1
/
pp.15-26
/
2002
The purpose of this study was to classier the somatotype of late middle-aged women and to analyze the characteristics of each somatotype. The subjects were 337 late middle-aged women and their age range os from 45 to 59 fears old. Data were collected through anthropometry and photometry and analyzed by factor analysis, cluster analysis and discriminant analysis. The results were as follows; 1. The result of factor analysis indicated that 9 factors were extracted through factor analysis and those factors comprised 83.56 percent of total valiance. 2. Using factor scores, cluster analysis was carried out and the subject were classified into 4 cluster. Each cluster was classified as their body front and side view contour. Type 1 is tall, slim, and lower balk is flat on the side. Type 2 is standard and lean-back type on the side. Type 3 is standard height and weight, H type in front, and belly-protruded on the side. Type 4 is short, fat, and the side is hip-protruded. 3. According to the stepwise discriminant analysis, the 9 important items in classifying the somatotype of the late middle-aged women are as follows ; lower back tilt angle, hip depth(back) -back waist depth(back), bust depth(fore) - anterior waist depth(fore), jugular fossa point(fore), upper back tilt angle, burst breadth -waist breadth, right shoulder tilt, height of shoulder - height of anterior waist, abdomen breath. The correct classification rate for these items is as exact as 84.62%.
An investigation was undertaken of the optimal discriminant model for predicting the likelihood of insolvency in advance for medium-sized firms based on the technology evaluation. The explanatory variables included in the discriminant model were selected by both factor analysis and discriminant analysis using stepwise selection method. Five explanatory variables were selected in factor analysis in terms of explanatory ratio and communality. Six explanatory variables were selected in stepwise discriminant analysis. The effectiveness of linear discriminant model and logistic discriminant model were assessed by the criteria of the critical probability and correct classification rate. Result showed that both model had similar correct classification rate and the linear discriminant model was preferred to the logistic discriminant model in terms of criteria of the critical probability In case of the linear discriminant model with critical probability of 0.5, the total-group correct classification rate was 70.4% and correct classification rates of insolvent and solvent groups were 73.4% and 69.5% respectively. Correct classification rate is an estimate of the probability that the estimated discriminant function will correctly classify the present sample. However, the actual correct classification rate is an estimate of the probability that the estimated discriminant function will correctly classify a future observation. Unfortunately, the correct classification rate underestimates the actual correct classification rate because the data set used to estimate the discriminant function is also used to evaluate them. The cross-validation method were used to estimate the bias of the correct classification rate. According to the results the estimated bias were 2.9% and the predicted actual correct classification rate was 67.5%. And a threshold value is set to establish an in-doubt category. Results of linear discriminant model can be applied for the technology financing banks to evaluate the possibility of insolvency and give the ranking of the firms applied.
The purpose of this study was to identify the college students'frequent usage groups of Western style restaurant in Ansan city. 200 samples among subjects were utilized for the analysis, and 150 samples were reserved far validating the discriminant function. Crosstabs, reliability analysis, stepwise discriminant analysis, and anova analysis were used for this study. The findings from this study were as follows. First, the result suggested that the four variables were important in discriminating the frequent usage group. Second, the result suggested that each discriminating variable between frequent usage groups was different significantly. Third, the result suggested that each usage situation between frequent usage groups was different significantly. Finally the study indicated the implications that could be provided some insight into the types of marketing strategies that can be successfully used by operators who manage Western style restaurants.
Journal of Physiology & Pathology in Korean Medicine
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v.25
no.1
/
pp.138-143
/
2011
In spite of abundant clinical resources of stroke patients, the objective and logical data analyses or diagnostic systems were not established in oriental medicine. As a part of researches for standardization and objectification of differentiation of syndromes for stroke, in this present study, we tried to develop the statistical diagnostic tool discriminating the 4 subtypes of syndrome differentiation using the essential indices considering the sex. Discriminant analysis was carried out using clinical data collected from 1,448 stroke patients who was identically diagnosed for the syndrome differentiation subtypes diagnosed by two clinical experts with more than 3 year experiences. Empirical discriminant model(V) for different sex was constructed using 61 significant symptoms and sign indices selected by stepwise selection. We comparison. We make comparison a between discriminant model(V) and discriminant model(IV) using 33 significant symptoms and sign indices selected by stepwise selection. Development of statistical diagnostic tool discriminating 4 subtypes by sex : The discriminant model with the 24 significant indices in women and the 19 significant indices in men was developed for discriminating the 4 subtypes of syndrome differentiation including phlegm-dampness, qi-deficiency, yin-deficiency and fire-heat. Diagnostic accuracy and prediction rate of syndrome differentiation by sex : The overall diagnostic accuracy and prediction rate of 4 syndrome differentiation subtypes using 24 symptom and sign indices was 74.63%(403/540) and 68.46%(89/130) in women, 19 symptom and sign indices was 72.05%(446/619) and 70.44%(112/159) in men. These results are almost same as those of that the overall diagnostic accuracy(73.68%) and prediction rate(70.59%) are analyzed by the discriminant model(IV) using 33 symptom and sign indices selected by stepwise selection. Considering sex, the statistical discriminant model(V) with significant 24 symptom and sign indices in women and 19 symptom and sign indices in men, instead of 33 indices would be used in the field of oriental medicine contributing to the objectification of syndrome differentiation with parsimony rule.
In this paper, statistical approach is undertaken to investigate the classification of wear debris which is the key function of objective assessment of wear debris morphology. Wear tests are run to produce various kinds of wear debris. The images of wear debris from wear tests are captured with image acquisition equipment. By thresholding, two-dimensional binary images of wear debris are made and, then, morphological parameters are used to quantify the images of debris. Parametric and nonparametric discriminant method are employed to classify wear debris into predefined wear conditions. It is demonstrated that classification accuracy of parametric and nonparametric discriminant method is similar. The selected use of morphological parameters by stepwise discriminant analysis can generally improve the classification accuracy of parametric and nonparametric discriminant method.
The purpose of this study was to investigate the possibility of discriminating a high level of school adjustment in low-income school-aged children using interpersonal-related variables(mother attachment, peer attachment) and self-related variables(ego-resiliency, self-control). The subjects were 335 children in fourth, fifth and sixth grades in 4 elementary schools in Daegu. Mean(SD), t-test, and stepwise discriminant analysis were used for data analysis. Base on the results of the discriminant analysis, the discriminant functions suggested that the best predictor for distinguishing between a high level of school adjustment in low-income school-aged children and a low level of school adjustment was ego-resiliency. Self-control, mother attachment and peer attachment reliably separated the groups. And using ego-resiliency, self-control, mother attachment and peer attachment as predictors, the discriminant analysis correctly classified 92.3% of the participants.
Journal of the Korean Society of Clothing and Textiles
/
v.25
no.8
/
pp.1386-1397
/
2001
The purpose of this study was to classify and analyze the somatotype of early middle-aged women and to provide its total data for clothing construction, and to improve clothing culture. The subjects were 277 early middle-aged women between 35 and 44 years old. Data were collected through anthropometry and photometry and analyzed by factor analysis, cluster analysis and discriminant analysis. The results were as follows; 1. The result of factor analysis indicated that 10 factors were extracted through factor analysis and those factors comprised 86.13 percent of total variance. 2. Using factor scores, cluster analysis was carried out and the subject were classified into 4 cluster. Type 1 is tall, slim, and X type in front. Type 2 is standard height and weight, short upper body, and hip-protruded on the side. Type 3 is standard height, thin, H type in front, back and hip are clearly protruded, and lean-back type on the side. Type 4 is standard height, fat, and long upper body. 3. According to the stepwise discriminant analysis, the 8 important iems is classifying the somatotype of early middle-aged women are as follows : bust girth, back length hip breadth-waist breadth, back protruded point depth(back)-back waist depth(back), hip tangent tilt, hip depth(back) waist dapth(back), bust depth-waist depth, and cervical hight, The correct classification rate for these items is as exact as 83.20%.
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