3 resultados para multiple linear regression

em Brock University, Canada


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Background: The purpose of this study was to examine the relationships between physical activity and healthy eating behaviour with the participant's motives and goals for each health behaviour. Methods: Participants (N 121; 93.2% female) enrolled in commercial weightloss programs at the time of data collection, completed self-reported instruments using a web-based interface that were in accordance with Deci and Ryan's (2002) Self-Determination Theory (SDT). Results: Multiple linear regression models revealed that motivation and goals collectively accounted for between 0.21 to 0.29 percent and 0.03 to 0.16 percent of the variance in physical and healthy eating behaviours in this sample. In general, goals regarding either behaviour did not appear to have strong predictive relationships with each health behaviour beyond the contributions of motives. Discussion: Overall, findings from this study suggest that motives seem to mattermore than goals for both physical activity and healthy eating behaviour in clientele of commercial weight-loss programs. Therefore commercial weight-loss program implementers may want to consider placing more attention on motives I than goals for their clientele when designing weight-loss and weight-maintenance initiatives.

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Children with developmental coordination disorder (DCD) are often referred to as clumsy because of their compromised motor coordination. Clumsiness and slow movement performances while scripting in children with DCD often result in poor academic performance and a diminished sense of scholastic competence. This study purported to examine the mediating role of perceived scholastic competence in the relationship between motor coordination and academic performance in children in grade six. Children receive a great deal of comparative information on their academic performances, which influence a student's sense of scholastic competence and self-efficacy. The amount of perceived academic self-efficacy has significant impact on academic performance, their willingness to complete academic tasks, and their self-motivation to improve where necessary. Independent t-tests reveal a significant difference (p < .001) between DCD and non-DCD groups when compared against their overall grade six average with the DCD group performing significantly lower. Independent t-tests found no significant difference between DCD and non-DCD groups for perceived scholastic competence. However, multiple linear regression analysis revealed a significant mediating role of 15% by perceived scholastic competence when examining the relationship between motor coordination and academic performance. While children with probable DCD may not rate their perceived scholastic competence as less than their healthy peers, there is a significant mediating effect on their academic performance.

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The effects. of moisture, cation concentration, dens ity , temper~ t ure and grai n si ze on the electrical resistivity of so il s are examined using laboratory prepared soils. An i nexpen si ve method for preparing soils of different compositions was developed by mixing various size fractions i n the laboratory. Moisture and cation c oncentration are related to soil resistivity by powe r functions, whereas soil resistiv ity and temperature, density, Yo gravel, sand , sil t, and clay are related by exponential functions . A total of 1066 cases (8528 data) from all the experiments were used in a step-wise multiple linear r egression to determine the effect of each variable on soil resistivity. Six variables out of the eight variables studied account for 92.57/. of the total variance in so il resistivity with a correlation coefficient of 0.96. The other two variables (silt and gravel) did not increase the · variance. Moisture content was found to be - the most important Yo clay. variable- affecting s oil res istivi ty followed by These two variables account for 90.81Yo of the total variance in soil resistivity with a correlation ~oefficient ·.of 0 . 95. Based on these results an equation to ' ~~ed{ ct soil r esist ivi ty using moisture and Yo clay is developed . To t est the predicted equation, resistivity measurements were made on natural soils both in s i tu a nd i n the laboratory. The data show that field and laboratory measurements are comparable. The predicted regression line c losely coinciqes with resistivity data from area A and area B soils ~clayey and silty~clayey sands). Resistivity data and the predicted regression line in the case of c layey soils (clays> 40%) do not coincide, especially a t l ess than 15% moisture. The regression equation overestimates the resistivity of so i l s from area C and underestimates for area D soils. Laboratory prepared high clay soils give similar trends. The deviations are probably caused by heterogeneous distribution of mo i sture and difference in the type o f cl ays present in these soils.