Use Of Stepwise Multiple Regression Research Articles

Assessment of the rate of human aging by clinical biochemical tests

The aim of the study was the development of the accessible method for assessing the rate of human aging by laboratory biochemical parameters. There were examined 408 practically healthy people in the age from 20 to 80 years. There were determined 6 anthropometric and 14 laboratory biochemical parameters, characterizing carbohydrate and fat metabolism, liver and kidney functions.The use of stepwise multiple regression made it possible to select the most informative indicators and obtain an equation linking the age of the examined people with a number of anthropometric and metabolic indicators. The average absolute error in calculating age was 4.2 years.The method for assessing the rate of aging, developed by us, is highly accurate and can be used to assess the risk of developing of the age-dependent pathology.

Why do only some SMEs achieve external support for better innovation performance: empirical evidence from Bangalore, India

Small and medium enterprises (SMEs) share unique characteristics of innovation and are simultaneously bounded by resource constraints. This study probes the role of internal factors in SMEs to obtain external support from government-promoted SME agencies, large enterprises, R&D institutes, universities, and other SMEs to achieve better innovation performance in the context of autocomponent, electronics, and machine tool industries in Bangalore in India. Using a stepwise logistic regression analysis, this study found that SMEs could obtain external support if they have internal technical competence (in terms of a technically qualified entrepreneur, an exclusive design centre, and frequent product or product & process innovation). The use of stepwise multiple regression showed that SMEs are able to exhibit superior innovation performance if they implement innovative ideas (or exploit market opportunities) and obtain external support with technically qualified entrepreneurs. Therefore, policy support to enhance the firm-level technical competence of SMEs and strengthen the external support infrastructure for SMEs would be beneficial.

Estimating travel reduction associated with the use of telemedicine by patients and healthcare professionals: proposal for quantitative synthesis in a systematic review

BackgroundA major benefit offered by telemedicine is the avoidance of travel, by patients, their carers and health care professionals. Unfortunately, there is very little published information about the extent of avoided travel. We propose to undertake a systematic review of literature which reports credible data on the reductions in travel associated with the use of telemedicine.MethodThe conventional approach to quantitative synthesis of the results from multiple studies is to conduct a meta analysis. However, too much heterogeneity exists between available studies to allow a meaningful meta analysis of the avoided travel when telemedicine is used across all possible settings. We propose instead to consider all credible evidence on avoided travel through telemedicine by fitting a linear model which takes into account the relevant factors in the circumstances of the studies performed. We propose the use of stepwise multiple regression to identify which factors are significant.DiscussionOur proposed approach is illustrated by the example of teledermatology. In a preliminary review of the literature we found 20 studies in which the percentage of avoided travel through telemedicine could be inferred (a total of 5199 patients). The mean percentage avoided travel reported in the 12 store-and-forward studies was 43%. In the 7 real-time studies and in a single study with a hybrid technique, 70% of the patients avoided travel. A simplified model based on the modality of telemedicine employed (i.e. real-time or store and forward) explained 29% of the variance. The use of store and forward teledermatology alone was associated with 43% of avoided travel. The increase in the proportion of patients who avoided travel (25%) when real-time telemedicine was employed was significant (P = 0.014). Service planners can use this information to weigh up the costs and benefits of the two approaches.

Assessing water quality by remote sensing in small lakes: the case study of Monticchio lakes in southern Italy

Abstract: In order to investigate bio-physical parameters associated with water quality, a model based on calibrated and atmospherically corrected Remotely Sensed data has been implemented. Secchi Disk depth and chlorophyll concentration parameters were estimated in a system of very small lakes at Monticchio (Italy) using Landsat TM data. The model was developed through the use of stepwise multiple regression and gave high coefficients of determination (R2 = 0.82 for Secchi Disk and R2 = 0.72 for chlorophyll). Values for water transparency were strongly correlated with chlorophyll a concentration: a linear relationship between the two parameters showed a high coefficient of determination (R2 = 0.93). The case study shows that the application of this approach on lakes with a small surface area, such as the Monticchio lakes in Southern Italy, is effective and the developed model well describes the water quality parameters.

Early prediction of the shelf-life of medium-heat whole milk powders using stepwise multiple regression and principal component analysis

Abstract Fifteen medium-heat whole milk powders manufactured at the same plant under identical processing conditions from 15 different batches of raw milk were subjected to accelerated storage at 50 °C and a water activity of 0.31 in air. With a view to the development of a new prediction method, 22 chemical and technological variables and 13 time-dependent changes over 2 days were measured at the beginning of the experiment. The development of oxidized flavour in the stored powders was subsequently assessed weekly for 6 weeks by a sensory panel. The shelf-life of each powder was determined as the time at which the mean flavour score crossed a threshold value (8 or 6 on a scale from 15 to 0). The relationship between shelf-life and the properties of the fresh powders, together with the time-dependent changes, was investigated by the use of Stepwise multiple regression with maximum R2 improvement, and pseudo-optimal sets of regression equations were found which minimized the PRESS (predicted sum of squares) statistic. The initial time-dependent change of TBA-reactive substances was the variable which correlated best (r = −0.66) with the shelf-life at flavour threshold 8, followed by the yellowness Hunter b-value of the powder (r = 0.54), while the variables which alone correlated best with the shelf-life at flavour threshold 6 were the density of milk powder after 1250 tappings (r = 0.58), TBA-reactive substances (r = −0.56), and the density of milk powder after 100 tappings (r = 0.53). The variables selected by PRESS minimization for the regression equation of threshold 8 (R2 = 0.949) were the α-lactalbumin content, the time-dependent change in β-lactoglobulin, the time-dependent change in TBA-reactive substances, the density after 1250 tappings, and the solubility index. The variables selected for the regression equation of threshold 6 (R2 = 0.980) were the α-lactalbumin content, the time-dependent change in β-lactoglobulin, the density after 1250 tappings, the total fat content, the time-dependent change in the redness Hunter a-value of the powder, and the initial moisture content. Good predictive abilities of the regression equations were indicated by small PRESS values, and the method appears ready for validation in industrial production. Differences between the milk powders were recognized by principal component analysis. One powder deviated clearly, but not extremely, from the other 14 powders on the first and second principal components, mainly because of a large initial amount of free radicals, a rapid generation of further free radicals, and a low initial concentration of fluorescent oxidation products. The first 7 principal components explained only 84% of the total variation, and no other groupings of the milk powders were apparent.

Comparison of three methods of profile change prediction in the adult orthodontic patient

Potential changes in the contour of the facial profile that accompany tooth movement can be important considerations in developing an orthodontic treatment plan. The objective of this study was to compare the accuracy of three different methods of predicting horizontal soft-tissue changes. Eighty-three nongrowing, orthodontically treated patients comprised the sample. Pretreatment and posttreatment lateral cephalometric hard- and soft-tissue landmark points were digitized. A coordinate system was defined, landmark coordinates were corrected for magnification, and then hard- and soft-tissue, angular, and linear measures were calculated by computer programs developed on a DEC PDP 11/44. The accuracy of prediction of soft-tissue landmark changes was compared for three prediction methods: (1) use of ratios of means of soft-tissue changes to corresponding hard-tissue changes, (2) use of a bivariate regression equation on corresponding hard-tissue landmark changes, and (3) use of stepwise multiple regression with hard-tissue changes and initial hard- and soft-tissue facial characteristics as predictor variables. For predicting changes of four soft-tissue points, multiple regression equations were slightly more accurate than ratio of means predictions. The standard errors of the estimate ranged from 0.7 to 1.1 mm for the multiple regression predictions; these were from 0.2 to 1.4 mm lower than those obtained for ratio of means predictions. The accuracy of the bivariate regression prediction technique fell between that of the other two methods. Examination of the residuals showed that the multiple regression equations consistently underpredicted the most extreme soft-tissue facial changes.

The Effect of Organizational Climate on Job Satisfaction, Anxiety, and Propensity to Leave

SummaryThis study examined the prediction of job-related attitudes from organizational climate dimensions. Ss were 111 supermarket department managers who returned an anonymous questionnaire which tapped perceptions of the organizational environment (i.e., climate) along 11 dimensions and also contained measures of job satisfaction, propensity to leave, and job-related anxiety. Each attitude variable was regressed on the 11 climate dimensions with use of stepwise multiple regression. The dimension of “Organizational clarity” emerged as the most significant predictor for each of the three outcome variables, a finding that is congruent with previous research in the area of role ambiguity. The dimension of “Performance-reward dependence” contributed significantly to the prediction of job satisfaction and propensity to leave, but not to the prediction of job-related anxiety. This is consistent with theories linking dissatisfaction and turnover with unsatisfactory reward systems.

The Effect of Ammoniacal Nitrogen on Lettuce (Lactuca sativa) and Radish (Raphanus sativus) Plants

AbstractThe relationship of the growth of radish and lettuce plants to pH, NH3, and NH4+ concentration of the nutrient solution was determined by the use of stepwise multiple regression. Data were collected from plants grown in nutrient solutions with a factorial arrangement of pH (6, 7, and 8) and ammonical nitrogen (0, 10, 20, 30, 40, 60, and 90 ppm of N). The equations obtained for radish and lettuce, respectively, were: Y = 0.479 + 0.00242 X13 + 0.0207 X2 − 0.605 X3 + 0.0133 X33 + 0.0200 X4 − 0.000746 X42 + 0.00000551 X43 and Y = 5.571 − 0.551 X1 − 0.00111 X23 − 0.605 X3 + 0.0171 X33 + 0.0428 X4 − 0.000753 X42 + 0.00000327 X43 where Y was grams of dry matter/plant, X1 was pH, X2 was H+ cone x 107, X3 was NH3 conc. (ppm of N) and X4 was NH4+ conc. (ppm of N). Both equations were significant at the 0.5% level and had R2's of 0.575 and 0.646, respectively. The response of the two species to pH and H+ differed, with radish having its optimum growth at pH 8 and lettuce at pH 7. Their responses to NH3 and NH4+ were very similar. Growth was reduced as the NH3 conc. increased and was increased as the NH4+ conc. increased to an optimum level of 17 ppm of NH4+‐N for radish and 36 ppm for lettuce.