Multiple Regression Equations For Prediction Research Articles

Development of a multiple regression equation for prediction of bearing capacity of geocell-reinforced sand beds based on experimental study

Development of a multiple regression equation for prediction of bearing capacity of geocell-reinforced sand beds based on experimental study

Modeling and Mapping of Salt-Affected Soils through Spectral Indices in Inland Plains of Semi-arid Agro-Ecological Region

Mapping the salt-affected soils (SAS) through spectral indices derived from satellite imagery is essential for its monitoring at a frequent interval and for the management. Several salinity indices have been developed based on the combination of spectral bands for predicting soil salinity in the arid environment. Present study attempted to identify and map the salt-affected soils (SAS) in inland plains of semi-arid agro-ecological region of Tamil Nadu, India using satellite image (Resourcesat-1(IRS-P6) LISS IV). Vertisols and Inceptisols are the major soil orders cultivated under paddy, sugarcane and pulses. An integrated approach of spectral bands and indices along with analytical data of samples collected from the field was used to develop multiple regression equations for prediction. The best linear regression model was selected based on adjusted R2 and MSE values for the prediction of pH, EC, and ESP. The variation observed between salt-affected soils predicted by multiple regression equations and measured data were 15, 10, and 5 percent for pH, EC, and ESP, respectively, due to weak variation in soil properties, sample density, better vegetation cover by management practices.

Relationship and Prediction of Body Weight from Morphometric Traits in Maefur Goat Population in Tigray, Northern Ethiopia

The study was conducted in Erob district eastern zone of Tigray, Northern Ethiopia to determine the relationship between live weight and linear measurements in Maefur goat population under traditional management system. Data on live body weight, linear body measurement and physical body character were collected from randomly selected 600 (297 male and 303 female goats) and categorized into age group of 04-12, 13-18, 19-24, and 24-35 months equivalent with to 0 PPI, 1 PPI, 2 PPI and 3 ≥ PPI with 82, 87, 134 and 297 animals in each age groups, respectively. The data were analyzed using SPSS software 16.0 version. Descriptive statistics, correlation and regression analysis were used. Heart girth was highly correlated to body weight (r=0.97, P<0.01) and used to predict live body weight with regression equations of y1.04 x-(43.3 ± 0.83), R²0.93 for pooled sex and age. The multiple regression equation for prediction of the live body weight was y=(0.74 HG+0.16 BL+0.18 HW) - 42.8, R2=0.95 for pooled sex and age. It was concluded that, there is variability in body measurements across sex and age indicated that these measurements could be exploited in predicting live body weight. Heart girth was the major body trait used to predict live body weight.

The relationship between cortical auditory evoked potentials (CAEPs) and speech perception in children with Nurotron® cochlear implants during four years of follow-up

ObjectiveThe purpose of the current study was to evaluate the relationship between the presence or absence of cortical auditory evoked potentials (CAEPs) to speech stimuli and the performance of speech perception in Chinese pediatric recipients of the Nurotron® cochlear implant (CI).We also wanted to determine how the CAEPs might be used as an indicator for predicting early speech perception and could provide objective evidence for clinical applications of CAEPs. Methods23 pediatric unilateral CI recipients participated in this study. 15 males 8 females, and their ages at implantation ranged from 13 to 68 months, with a mean age of 36 months. CAEPs and Mandarin Early Speech Perception (MESP) tests were used to evaluate the audibility and speech perception of these CI users. The tests were administered at the first, second, third, and fourth year after the CI surgery. ResultsAll the subjects demonstrated improvements in detection of speech sounds with CI. The percentages of participants who could detect all three stimuli were 26% (6/23) at first year, to 100% (23/23) at the fourth year post-implantation. The percentages of participants who passed the Category 6 of MESP were from 9% (2/23) at first year, to 91% (21/23) at the fourth year post-implantation. Significant correlations (p<0.05) were found between CAEP scores and MESP at the first, second, third year after the CI surgery. The multiple regression equation for prediction of MESP categories from CAEP scores and hearing ages was MESP=1.088+(0.504×CAEP score)+(0.964×hearing ages) (F=72.919, p<0.001, R2=0.621). ConclusionThe results of this study suggested that aided cortical assessment was a useful tool to evaluate the outcomes of cochlear implantation. Cortical outcomes had a significant positive relationship with the MESP, which predicted the early speech perception of CI recipients.

A Multiple Regression Equation for Prediction of Bearing Capacity of Geosynthetic Reinforced Sand Beds

Several researchers have studied the effects of various important parameters like number of layers of reinforcement (N), depth of the upper most layer of reinforcement from the base of the footing (u), spacing of the reinforcement layers (h), width of reinforcement layer (b), tensile strength of reinforcement (T) and density of soil (γ) on the ultimate bearing capacity of footings on reinforced soils. However, very few of them have attempted to develop equations to estimate the bearing capacity of the footings on reinforced soils by considering all the above parameters. Review of the existing state of the art in this area is presented in this paper and the ability of the existing analytical models to predict the ultimate bearing capacity of reinforced sand beds is verified using results from laboratory model tests. A multiple regression equation to estimate the ultimate bearing capacity of square footing resting on geosynthetic reinforced sand beds based on the laboratory model studies is presented. This equation is verified against the experimental results of model studies and also with the experimental measurements of other researchers. Statistical analysis of the model test data revealed that the aperture size of the reinforcement is very influential in altering the bearing capacity of reinforced sand beds. The regression equation developed in this study is reasonably good in predicting the bearing capacity of square footing on dense sand reinforced with planar geosynthetics.

Norms for the Wingate Anaerobic Test with Comparison to Another Similar Test

This study was undertaken in order to develop norms for the Wingate test for physically active young men and women, and also to compare mean power measures obtained from the Wingate test with those obtained from another similar cycle ergometer test. A total of 112 males and 74 females aged 18 to 28 years comprised the subject pool. Data collected from the Wingate test included mean power for 30 s, peak power for 5 s, and a percent fatigue index. Data from the second test (Katch test) included mean power for both 30 s and 40 s. Percentile norms and descriptive statistics were generated as were multiple regression equations for prediction of mean power between the two different tests. Correlations between the two tests ranged from .66 to .87. Comparisons among data derived from this study and those reported for other athletic groups are also given.

A multiple regression equation for prediction of posthepatectomy liver failure.

This article reports a multiple regression equation for prediction of posthepatectomy liver failure. In phase I, using the correlations between 17 preoperative parameters (Xi) and the postoperative course scored (Y) of the past 36 hepatectomized patients, we proposed the following multiple regression equation: Y = -110 + 0.942 X resection rate (%) + 1.36 X ICG retention rate (%) + 1.17 X patient's age + 5.94 X ICG maximal removal rate (mg/kg/min). With the equation, the calculated Y value (prediction score) of these patients revealed that prediction scores of the eight nonsurvivors with liver failure were more than 50 points while those of the 28 survivors were 50 points or less. In phase II, the relationships between early prognosis and a precalculated prediction score were prospectively found the same as that seen in phase I. These findings indicate that our formula is a useful prognostic index for prediction of posthepatectomy liver failure.

Hydrophobicity and Solubility of Meat Proteins and Their Relationship to Emulsifying Properties

ABSTRACTSurface hydrophobicity (So) of crude salt extracts of meat was determined fluorometrically using cis‐parinaric acid as a probe. Upon heating the extracts to 70°C, So increased two‐ to threefold, whereas protein solubility (s) decreased to 20%. Further heating (to 85°C) resulted in slight decreases in both So and s. Backwards stepwise multiple regression equations for prediction of emulsifying activity index (EAI) and emulsifying capacity (EC) were: EAI = 2.658 + 0.0001308 sSo, and EC =−35.30 + 6.459 s + 0.001317 sSo− 0.05463 s2. So was most important for predicting emulsifying properties of samples with high (&gt;50%) solubility, whereas solubility parameters were more influential for samples with low (&lt;50%) solubility.

Body composition in middle-aged women with special reference to the correlation between body fat mass and anthropometric data

A variety of anthropometric measurements was made in a randomized population sample of middle-aged women in five age strata in whom body composition was estimated from total body potassium and total body water determined by whole body counting and isotope dilution technique, respectively. No significant differences with age were found for total body potassium or total body water. A significant age difference was found for body fat mass. Simple linear correlations between anthropometric variables and body fat mass estimates were found to be 0.90, 0.86, 0.77 for body weight, buttock circumference, and sum of triceps and subscapular skinfold thicknesses, respectively. Multiple regression analysis showed that these three variables accounted for 80 to 91% of the variation in body fat in the different age strata studied. Multiple regression equations for prediction of body fat from anthropometric variables are given. In about two-thirds of the subjects, the difference between predicted body fat mass and estimated body fat mass was found to be less than ±2.5 kg.

Prediction of the mesiodistal widths of maxillary permanent canines and premolars

Multiple regression equations for prediction of the mesiodistal widths of the maxillary canines and premolars were developed for the right and left sides of the arches of males and females. The equations were developed from longitudinal data taken from ninety-two Caucasian children (forty-six boys and forty-six girls) who participated in the Iowa Growth Study. The multiple regression equations, when compared with three currently used methods of prediction, were the best predictors. The newly developed equations and other prediction methods currently in use were tested on longitudinal data taken from a sample of forty-three Caucasian orthodontic patients (sixteen males and twenty-seven females). Again, the multiple regression equations had the best performance.

Life history and mood as predictors of adjustment in navy recruit training

A Mood Questionnaire (MQ) and a Life History Questionnaire (LHQ) were completed by 1,292 Navy recruits shortly after beginning basic military training. The relationships of life history characteristics and reported moods to success or failure in recruit training were determined. One mood (self-reported Depression) and two LHQ factors (Social Participation and Antisocial Behavior) contributed uniquely to a multiple regression equation for prediction of effectiveness in recruit training. The reported moods of Happiness and Depression, and the Social Participation factor were found to differ significantly between discharged and nondischarged recruits who were matched for antisocial behavior. The application of these results in identifying recruits who may benefit most from counseling and remediation programs, as well as modifying current measures of long-term military effectiveness, was discussed.

Formulation of Hay-Grain Diets for Ruminants I. Evaluation of Multiple Regression Equations for Prediction of Bermudagrass Hay Quality from Laboratory Analyses2

Formulation of Hay-Grain Diets for Ruminants I. Evaluation of Multiple Regression Equations for Prediction of Bermudagrass Hay Quality from Laboratory Analyses2