Small Standard Error Of Estimate Research Articles

Estimation of Rhizophora mucronata carbon stock in Youtefa bay, Jayapura, Papua

Papua island has the largest mangrove forest area in Indonesia, reaching 1,350,600.00 Ha which accounts for half of the entire area of mangrove forests in Indonesia. One of the locations with a fairly extensive mangrove forest in the Jayapura area is in Youtefa Bay. Although mangroves have large environmental potential, local people use the forest as building materials, food, fishing tools, and medicines. Mangrove forests have an active role in maintaining global climate stability in the world, forest vegetation will fix CO2 through the process of photosynthesis. Mangrove forests per hectare can store up to four times more carbon than other tropical forests worldwide. This research aims to estimate the amount of carbon stock Rhizophora mucronata can store in mangrove forests in Youtefa Bay, particulary in Tobati, Enggros and Entrop Villages, Jayapura, Papua. The method used in this study was using Allometric Equations to estimate the biomass carbon from Rhizophora mucronata and compared to three different satellite imagery algorithms. The research results showed that the biomass of Rhizophora mucronata stands in Entrop Village was the highest and the lowest in Enggros Village. In addition, the results of measurements of carbon stocks in Tobati and Enggros Villages showed that the values were similar, only 0.23 kgC/m2 with carbon stocks in Entrop Village reaching 19.46 kgC/m2. Based on the results of measuring satellite imagery with three different algorithms, it was found that using the EVI algorithm produced the smallest Standard Error of Estimate, which was 1.63 kg C/m2. The estimated total carbon in Youtefa Bay is 213,424.69 kg C/m2.Keywords:AllometricCarbon StockRhizophora mucronataYoutefa Bay

Factors influencing gait speed in community-dwelling older women: A Bayesian approach

BackgroundHuman gait is a complex task resulting from the interaction of sensory perception, muscle force output, and sensory-motor integration, which declines with the aging process and impacts gait speed in older women. Research questionWhat are the separate and combined impacts of sensory-motor factors on gait speed of older women? MethodsSixty healthy older women (69.3 ± 5.9 years) volunteered for this study. A previous screening using Pearson’s correlation selected variables significantly correlated with gait speed: age, plantar tactile perception, lower limb explosive force, and mean velocity (MV) of the center of pressure (CoP). Simple and multivariate regression models were performed with selected variables. The magnitude of evidence was obtained using Bayesian inference, determining posterior probabilities based on our data. ResultsGait speed was negatively correlated with age and positively correlated with plantar tactile perception, MV (Romberg index), and lower limb explosive force. The coefficient of determination (R2) varied between 0.06 for plantar tactile perception and 0.22 for explosive force (p < 0.05). The multivariate model, including age, MV (Romberg index), and lower limb explosive force, explained 44% (R2 = 0.44) of the variance in gait speed, with a small standard error of estimate (0.14 m/s). Bayesian inference confirmed the good posterior probability of the model. SignificanceAge, plantar tactile perception, MV (Romberg index), and lower limb explosive force impact gait speed, whereas the combination of the first three factors has an excellent posterior probability of predicting or affecting gait speed.

Age estimation by evaluation of osteophytes in thoracic and lumbar vertebrae using postmortem CT images in a modern Japanese population.

Estimation of age at death is important in forensic investigations of unknown remains. There have been several reports on applying the degree of osteophyte formation-an age-related change in the vertebral body-for age estimation; however, this method is not yet established. This study investigated a method for age estimation of modern Japanese individuals using osteophytes measured on CT images. The sample included 250 cadavers (125 males) aged 20-95years. The degree of osteophyte formation was evaluated as score O (0-5 points), and the degree of fusion of the osteophytes between the upper and lower vertebrae was evaluated as score B (0-2 points). Age estimation equations were developed using regression analyses with seven variables, determined by scores O and B, and the equation with the smallest standard error of estimate (SEE) was obtained when the number of vertebrae with score O ≥ 2 was used as the explanatory variable. Age estimation with SEE of about 10years was possible even when partial vertebrae with a high degree of osteophyte formation were used, showing its potential for practical application. The cutoff value for age estimation was established using the receiver operating characteristic curve analysis, wherein good results were obtained for all variables (area under the curve ≥ 0.8). The combination of the estimation equation and the cutoff value can narrow the range of age estimates.

Application of Artificial Neural Networks to Assess Student Happiness

The purpose of this study is to develop an analytical assessment approach to identify the main factors that affect graduate students' happiness level. The two methods, multiple linear regression (MLR) and artificial neural networks (ANN), were employed for analytical modelling. A sample of 118 students at a small non-profit private university constituted the survey pool. Various factors including education, school facilities, health, social activities, and family were taken into consideration as a result of literature review in happiness assessment. A total of 32 inputs and one output variables were identified during survey design phase. The following survey conduction, data collection, cleaning, and preparation; MLR and ANNs were built. ANN models provided better classification performance with over 0.7 R-square and a smaller standard error of estimate compared to MLR. Major policy areas to improve student happiness levels were identified as career services, financial aid, parking and dining services.

Application of artificial neural networks to assess student happiness

The purpose of this study is to develop an analytical assessment approach to identify the main factors that affect graduate students' happiness level. The two methods, multiple linear regression (MLR) and artificial neural networks (ANN), were employed for analytical modelling. A sample of 118 students at a small non-profit private university constituted the survey pool. Various factors including education, school facilities, health, social activities, and family were taken into consideration as a result of literature review in happiness assessment. A total of 32 inputs and one output variables were identified during survey design phase. The following survey conduction, data collection, cleaning, and preparation; MLR and ANNs were built. ANN models provided better classification performance with over 0.7 R-square and a smaller standard error of estimate compared to MLR. Major policy areas to improve student happiness levels were identified as career services, financial aid, parking and dining services.

Estimating body mass and composition from proximal femur dimensions using dual energy x-ray absorptiometry

Body mass prediction from the skeleton most commonly employs femoral head diameter (FHD). However, theoretical predictions and empirical data suggest the relationship between mass and FHD is strongest in young adults, that bone dimensions reflect lean mass better than body or fat mass and that other femoral measurements may be superior. Here, we generate prediction equations for body mass and its components using femoral head, neck and proximal shaft diameters and body composition data derived from dual-energy x-ray absorptiometry (DXA) scans of young adults (n = 155, 77 females and 78 males, mean age 22.7 ± 1.3 years) from the Andhra Pradesh Children and Parents Study, Hyderabad, India. Sex-specific regression of log-transformed data on femoral measurements predicted lean mass with smaller standard errors of estimate (SEEs) than body mass (12–14% and 16–17% respectively), while none of the femoral measurements were significant predictors of fat mass. Subtrochanteric mediolateral shaft diameter gave lower SEEs for lean mass in both sexes and for body mass in males than FHD, while FHD was a better predictor of body mass in women. Our results provide further evidence that lean mass is more closely related to proximal femur dimensions than body or fat mass and that proximal shaft diameter is a better predictor than FHD of lean but not always body mass. The mechanisms underlying these relationships have implications for selecting the most appropriate measurement and reference sample for estimating body or lean mass, which also depend on the question under investigation.

Influence of regression model and incremental test protocol on the relationship between lactate threshold using the maximal-deviation method and performance in female runners

This study examined the influence of the regression model and initial intensity of an incremental test on the relationship between the lactate threshold estimated by the maximal-deviation method and the endurance performance. Sixteen non-competitive, recreational female runners performed a discontinuous incremental treadmill test. The initial speed was set at 7 km · h−1, and increased every 3 min by 1 km · h−1 with a 30-s rest between the stages used for earlobe capillary blood sample collection. Lactate-speed data were fitted by an exponential-plus-constant and a third-order polynomial equation. The lactate threshold was determined for both regression equations, using all the coordinates, excluding the first and excluding the first and second initial points. Mean speed of a 10-km road race was the performance index (3.04 ± 0.22 m · s−1). The exponentially-derived lactate threshold had a higher correlation (0.98 ≤ r ≤ 0.99) and smaller standard error of estimate (SEE) (0.04 ≤ SEE ≤ 0.05 m · s−1) with performance than the polynomially-derived equivalent (0.83 ≤ r ≤ 0.89; 0.10 ≤ SEE ≤ 0.13 m · s−1). The exponential lactate threshold was greater than the polynomial equivalent (P < 0.05). The results suggest that the exponential lactate threshold is a valid performance index that is independent of the initial intensity of the incremental test and better than the polynomial equivalent.

Estimation of stature from static and dynamic footprints

The ability to estimate accurately from known parameters is a fundamental aspect of science and is evident as an emerging approach in the area of footprints and stature estimation within the field of forensic identification. There are numerous foot dimensions that have been measured in the literature to predict stature with varying degrees of confidence but few studies have tried to link the strength of estimation to anatomical landmarks. Such an approach is utilised in this study which estimates stature from the right footprints of sixty one adult male and female UK participants. Static and dynamic footprints were taken from each volunteer using the 'inkless paper system'. The prints were digitised and twelve length, width and angle measurements were chosen for the analysis. The highest correlations with stature were shown to be the heel to fourth toe print for the static group of footprints (r=0.786, p<0.01), and the heel to fifth toe print in the dynamic footprints (r=0.858, p<0.01). Collinearity statistics suggest the heel to fifth toe print length measurement is independent and not influenced by any other variables in the estimation of stature for the dynamic prints. Linear regression equations for this measurement presented the smallest standard error of estimate (SEE) and highest shared variance (R(2)) of all included variables (SEE 4.16, R(2) 0.74). Our study discusses a potential anatomical explanation as to why the lateral border of the foot and hence the impression it makes upon a hard surface, is a more stable indicator in the estimation of stature. The investigation recommends the use of Calc_A4 and Calc_A5 length measurements when estimating stature from footprint impressions.

Precisão das equações preditivas de 1-RM em praticantes não competitivos de treino de força

The purpose of this study was to assess the precision of the 1-RM prediction equations proposed by Adams (1994), Baechle and Groves (2000), Brzycki (1993), Epley (1985), Lander (1985) and O’Conner et al. (1989) for strength assessment in fitness programs. Thirty one healthy regular strength training male practitioners (mean ± SD: 21.8 ± 4.0 years of age; 75.9 ± 8.4 kg of weight; and 178.1 ± 6.4 cm of height) performed two tests on the bench press exercise: (a) maximum test - determination of the 1-RM load; and (b) submaximum test - determination of the load matching 4 to 10 maximum repetitions. Analysis of variance (ANOVA) found no significant difference (p > .05) between maximum load determination through prediction equations or through the 1-RM test. The coefficient of determination (r²) varied from .94 to .96. The prediction equations had small standard error of estimate (2.7 to 3.2 kg). Results indicate that the 1-RM prediction equations could be used to determine the maximum load at the bench press exercise in subjects with low strength training experience.

Stature and Body Weight Estimation from Various Footprint Measurements Among Egyptian Population

Analysis of footprints can reveal very important clues which can be used as a forensic evidence and help in the estimation of stature and body weight of an individual. In this work, bilateral footprints were obtained from 50 male Egyptian medical students ranging in age between 18 and 25. Nine measurements were taken on each footprint. The result revealed significant bilateral asymmetry (p < 0.001) except foot breadth at ball. The significant and positive highest correlation coefficients with stature were shown by toe-5 length on right side (R = 0.58) and with body weight by foot breadth at ball on left side (R = -0.52). Regression equations presented smaller standard errors of estimate (3.52-4.69) in determination of stature than those in estimation of body weight (4.05-5.28). In conclusion, this study has provided equations that help to estimate stature and body weight from footprint measurements among Egyptians.

Soy, isoflavones and prostate cancer risk in men: a meta‐analysis

Soy is a major plant source of dietary protein to humans. Epidemiologic studies show that soy consumption may be associated with a reduction in cancer risk in humans. The purpose of this study was to conduct a meta‐analysis on the association between soy and prostate cancer in men. We systematically reviewed studies obtained through a thorough MEDLINE literature search and identified 15 studies on soy consumption and eight on isoflavone intake in relation to prostate cancer risk. We conducted this analysis using a random‐effects model in which studies with smaller standard error of estimate are given greater weight in the summary measure. Our analysis of studies on soy intake yielded an overall risk estimate of 0.74 (95% confidence interval: 0.63, 0.89; P = 0.001). When separately analyzed, studies on non‐fermented soy foods yielded an overall risk estimate of 0.70 (0.56, 0.88; P = 0.002) and those on fermented ones yielded 1.02 (0.73, 1.42; P = 0.922). The analysis of studies on isoflavones yielded an overall risk estimate of 0.88 (0.76, 1.02; P = 0.085). When analyzed on the basis of daily isoflavone intakes, we found an overall risk estimate of 0.63 (0.41, 0.96; P = 0.03) from studies at mg/day and 0.99 (0.85, 1.16; P = 0.909) from those at µg/day, respectively. Results of this analysis suggest that consumption of soy foods is associated with a reduction in prostate cancer risk in men.

Queen's College Step Test as an Alternative of Harvard Step Test in Young Indian Women

Indian women often report premature exhaustion in the lower limb while performing the Harvard step test (HST) for measurement of physical fitness index (PFI) whereas they can easily perform the Queen's college step test (QCT). 155 sedentary females of 19-24 years were selected for the study from Institute of Dental Sciences, UP, India to evaluate the applicability of QCT as an alternative of HST. They were divided into study group (n=100) and confirmatory group (n=55). All subjects performed QCT comfortably but 35 (20 from study group and 15 from confirmatory group) of them could not properly perform the HST due to premature fatigue in their legs and therefore these 35 subjects were discarded from the study. Existence of significant correlation (r =-0.90, P <0.001) between PFI and QCT heart rate depicted the following prediction norm for PFI from QCT heart rate : Y=195.06-3.09 X (SEE=3.09). Prediction of PFI by this norm in the confirmatory group showed insignificant variation with the directly measured value from the HST. Bland and Altman's analysis also indicated that QCT norm predicts the PFI with 95% confidence interval. Moreover, QCT is easy to perform and the derived norm from QCT predicted the PFI score with substantially small standard error of estimate. Therefore, QCT is recommended as a valid and authentic test for evaluating PFI in young sedentary females of Uttar Pradesh, India.

Development and validation equation for estimate of Body Fat in Brazilian Army Military Men

Some indirect methods for the estimate of body fat and overweight have already been developed world-wide. They have low accuracy when used with soldiers of the Brazilian Army. PURPOSE: To develop and validate an equation for the estimate of body fat of Brazilian Army personnel, using few and simple variable measurements. METHODS: The sample was composed of 304 Army men (Age 34.37 + 11.14 yr, body mass (BM) 78.84 + 12.12 kg, stature 175.66 + 6.98 cm, waist girth (WG) 89.25 + 10.68 cm, percentage of body fat (% BF) 17.07+7.42 %, and Fat Mass (FM) 14.00 + 7.76 Kg). Corporal density was measured by means of the hydrostatic weight and transformed into % BF using the Siri equation (1961). In the equation validation the Multiple correlation Coefficient (R) and the Standard Error of Estimate (SEE) were considered, according to Lohman's recommendations (1992). Stepwise Regression Analysis was also used and the validation was carried out through the analysis of the residual equations. RESULTS: The results are shown in the following table 1:Table 1CONCLUSIONS: From the above table, it is possible to observe that it was possible to validate equations with only the WG, BM and age. The equations using the WG and the BM present the greatest R and the smallest SEE. The equations for the estimate of Fat Mass present very good R, but this does not increase with the inclusion of BM and little with age. Although the equations of F% present SEE greater the that recommended by Lohman (1992), the use of few variables facilitated and agilized obtaining results. However, in order to meet the objectives of this study, we recommend the use of equation 2 (F%, WG and BM), for in addition to the great correlation these possess with the quantity of fat, it can be related to coronary risk.

Interindividual variability in sleeping metabolic rate in Japanese subjects

Basal metabolic rate (BMR) or sleeping metabolic rate (SMR) is the largest component of total energy expenditure (EE). An accurate prediction of BMR or SMR is needed to accurately predict total EE or physical activity EE for each individual. However, large variability in BMR and SMR has been reported. This study was designed to develop prediction equations using body size measurements for the estimation of both SMR and BMR and to compare the prediction errors with those in previous reports. We measured body size, height, weight and body composition (fat mass and fat-free mass) from skinfold thickness in adult Japanese men (n=71) and women (n=66). SMR was determined as the sum of EE during 8 h of sleep (SMR-8h) and minimum EE during 3 consecutive hours of sleep (SMR-3h) measured using two open-circuit indirect human calorimeters. BMR was determined using a human calorimeter or a mask and Douglas bag. The study population ranged widely in age. The SMR/BMR ratio was 1.01+/-0.09 (range 0.82-1.42) for SMR-8h and 0.94+/-0.07 (range 0.77-1.23) for SMR-3h. The prediction equations for SMR accounted for a 3-5% larger variance with 2-3% smaller standard error of estimate (SEE) than the prediction equations for BMR. SMR can be predicted more accurately than previously reported, which indicates that SMR interindividual variability is smaller than expected, at least for Japanese subjects. The prediction equations for SMR are preferable to those for BMR because the former exhibits a smaller prediction error than the latter.

Use of Bioelectrical Impedance Analysis and Anthropometry to Measure Fat‐free Mass in Children and Adolescents With Crohn Disease

To investigate the precision of published prediction equations for fat-free mass (FFM) from bioimpedance measurements in children with Crohn disease using dual-energy X-ray absorptiometry (DXA) as an in vivo gold standard. Fat-free mass of 49 white boys and girls ages 7.3 to 16.9 y suffering from Crohn disease was measured by DXA. Body weight, height and bioimpedance measurements were also collected. FFM measured by DXA (FFM(DXA)) was compared with FFM predicted by the only 5 published prediction equations available for children and adolescents. An equation was developed for predicting FFM and was validated using a bootstrap method. When correlating predicted FFM with FFM(DXA), Schaefer's equation showed the highest R2 (0.950), the smallest standard error of estimate (SEE) (2.05 kg) and the smallest percentage error (0.28%). Our prediction equation for estimating FFM was FFM = 0.652 Ht2/Z + 0.0385 Wt + 0.586 Age - 0.327, R2 = 0.951, SEE = 2.08, P < 0.0005, where Ht2/Z is the impedance index in cm2/ohm, Wt is body weight in kilograms, age is in years. R2 value from bootstrap method was 0.950 +/- 0.01 (95% confidence interval 0.927-0.968), indicating an acceptable validation of the derived formula. The formula of Schaefer is the best for predicting FFM. The present study provides a new prediction equation for estimating FFM in children with Crohn disease that may be used in clinical settings in which more sophisticated body composition measuring equipments are not available.

Stature Estimation for Bosnian Male Population

Since 1996, the Trotter and Gleser formulae to determine the stature of recovered missing persons in Bosnia and Herzegovina have been used. The purpose of this study is to develop appropriate stature estimation formulae from the length of the femur, tibia and fibula for use in the Bosnia and Herzegovina to help in identifications of the victims. Research was undertaken on 50 male cadavers, of individuals who died between the ages of 23 to 54 years. The cadaver length was measured and the length of the long bones was obtained from X-ray photographs. The length of the cadavers of the individuals who died after age of 45 years was corrected according to Giles' table. This study established that using Trotter and Gleser's formulae underestimate stature of tall people in the current population of Bosnia and Herzegovina. Smallest standard error of estimate is observed in the formula that uses the sum of the length of femur and fibula. There are no statistically significant differences between the length of the bones from the left and right sides of the body. Therefore, formulae developed from the average length of bone pairs are recommended for use.

Evaluating Discrepancy Analyses With the Wisc-Iii and Wiat

Multiple regression was used to examine the predictive power of the four index scores of the Wechsler Intelligence Scale for Children-Third Edition (WISGIII; Wechsler, 1991) in forecast ing student achievement ( N = 300) as mea sured by the Wechsler Individual Achievement Test (WIAT; The Psychological Corporation, 1992). Separate equations were developed for each of the WIAT's composite scores (i.e., Total, Reading, Mathematics, Language, and Writing) using a forward-entry procedure. WISC-III index scores not found to contribute a significant amount of variance to each equa tion were removed. The stability of the result ing reduced equations was supported through cross-validation with an independent sample ( N= 208). Results indicate that the WISC-III's index scores provide better prediction of WIAT achievement composites than does the FSIQ and yield smaller standard errors of estimate. Separate equations are provided for predicting expected achievements for each of the WIAT composite scores.

Relative validity of clinical techniques for measuring the body composition of persons with amyotrophic lateral sclerosis

Tracking body composition is necessary to understand how amyotrophic lateral sclerosis (ALS) is affecting a patient's morphology and to provide a basis for appropriate nutritional advice throughout disease progression. Dual X-ray absorptiometry (DEXA) has been shown to reliably detect body composition changes in persons with ALS. However, this procedure is expensive and available primarily for research. The purpose of this study was to determine the relative validity of two common clinical techniques, anthropometry and bioelectrical impedance analysis (BIA), for measuring the body composition of persons with ALS. Twenty-three persons with ALS volunteered for the study; seven with primarily bulbar symptoms, five with primarily arm weakness, five with primarily leg weakness, and six with significant weakness in all extremities. On a single day subjects underwent body composition analysis by the three techniques, with DEXA serving as the criterion method. Anthropometry and BIA results were converted to lean and fat mass using eight prediction equations commonly cited in the literature. Anthropometry measures were also converted to estimates of muscle mass using two additional equations. Both BIA and anthropometry tended to overestimate lean mass and underestimate fat mass compared to DEXA. However, the BIA prediction equations had smaller mean differences, larger correlations, and smaller standard errors of estimate than the anthropometry equations. The Lukaski et al. BIA equation (Lukaski, H.C., Bolonchuk, W.W., Hall, C.B., Siders, W.A., 1986. Validation of tetrapolar bioelectrical impedance method to assess human body composition. J. Appl. Physiol. 60, 1327–1332) most closely matched the values derived by DEXA and is probably the best method for measuring the lean and fat mass of persons with ALS, as long as they maintain adequate hydration levels. The Heymsfield et al. equation (Heymsfield, S.B., McManus, C., Smith, J., Stevens, V., Nixon, D.W., 1982. Anthropometric measurement of muscle mass: revised equations for calculating bone-free arm muscle area. Am. J. Clin. Nutr. 36, 680–690) for estimating muscle mass may also be a useful clinical tool for this population. Further longitudinal studies are needed to determine whether the equations that correlated best with DEXA at a single point in time are also sensitive enough to detect changes in body composition over a period of time.

Doppler echocardiographic evaluation of pulmonary vascular resistance in children with congenital heart disease

Noninvasive assessment of pulmonary vascular resistance has not been well defined. Cardiac catheterization findings in 33 patients with congenital heart disease (mean age 1.4 years) were compared with Doppler echocardiographic parameters. The right ventricular pre-ejection period (RVPEP), ejection time (RVET), and the ratio RVPEP RVET correlated better with pulmonary vascular resistance than with pulmonary artery pressure. A highly significant correlation with a small standard error of estimate (SEE) was demonstrated between pulmonary vascular resistance and a newly derived parameter RVPEP/velocity time integral (VTI) [ r = 0.87, p < 0.0001, SEE = 2]. An RVPEP VTI value of <0.4 seconds/meter (M) was able to select patients with pulmonary vascular resistance <3 Wood Unit · M 2, even in the presence of pulmonary artery hypertension caused by increased pulmonary blood flow, with 97% accuracy (100% sensitivity, and 92% specificity). An RVPEP VTI value of 0.4 to 0.6 seconds/M identified patients with pulmonary vascular resistance between 3 to 7.5 Wood Unit · M 2 with 91% accuracy, and a value of ≥0.6 seconds/M selected patients with total pulmonary vascular resistance ≥7.5 Wood Unit · M 2 with 94% accuracy.

Estimation of Metabolic Rate Using Qualitative Job Descriptors

This project developed two methods to estimate metabolic rate that can be used easily and provide acceptable precision. The methods were developed from the measurement of oxygen consumption on 80 typical jobs in automotive manufacturing. The Ready-Reference Method uses three easily identified, dichotomous characteristics to classify the job into one of four levels of metabolic rate. The characteristics are based on motion of the hands, weights or forces, and walking; standard error of estimate was 68 kcal/hour. The Component Method has four terms that account for hand motion, walking/carrying, lifting, and pushing/pulling. Hand motions and lifting factors are characterized by three or four categories with a reference value to make the determination easier by using more qualitative data. Walking/carrying and pushing/pulling data are noted as typical distances traveled in one minute. The standard error of estimate for this method was 62 kcal/hour. In addition to a smaller standard error of estimate, the further advantage of the Component Method over the Ready-Reference Method is an ability to point toward the largest contributors to metabolic rate.