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Books on the topic 'Stepwise regressions'

Author: Grafiati

Published: 10 January 2023

Last updated: 28 January 2023

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1

Hinds, H. A. Third quarterly report on the application of modified stepwise regression for the estimation of aircraft stability and control parameters. Cranfield, Bedford: College of Aeronautics, Cranfield Institute of Technology, 1989.

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2

Cook, M. V. Initial review of research into the application of modified stepwise regression for the estimation of aircraft stability and control parameters. Cranfield, Bedford: College of Aeronautics, Cranfield Institute of Technology, 1989.

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3

Hinds, H. A. Review of initial experiments using the Hawk model, dynamic rig facility and the CED1401 digital data acquisition equipment. Cranfield, Bedford, England: Cranfield Institute of Technology, College of Aeronautics, 1990.

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4

Hinds, H. A. Measurement of the longitudinal static stability and the moments of 0inertia of a 1/12th scale model of a B.Ae Hawk. Cranfield, Bedford: College of Aeronautics, Cranfield Institute of Technology, 1990.

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5

On stepwise procedures for some multiple inference problems. Göteborg: Alqvist & Wiksell International, 1989.

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6

Hinds, H. A. Preliminary studies for aircraft parameter estimation using modified stepwise regression. Cranfield, Bedford, England: College of Aeronautics, Cranfield Institute of Technology, 1989.

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7

Hoff, J. C. Initial evaluation of the modified stepwise regression procedure to estimate aircraft stability and control parameters from flight test data. Cranfield, Bedford, England\: Cranfield University, College of Aeronautics, 1993.

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8

Billings, S. A. A prediction error and stepwise regression estimation algorithm for nonlinear systems. Sheffield: University, Dept. of Control Engineeering, 1985.

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9

Hinds, H. A. Second quarterly report on the application of modified stepwise regression for the estimation of aircraft stability and control parameters. Cranfield, Bedford, England: Cranfield Institute of Technology, College of Aeronautics, 1989.

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10

Cheng, Russell. Nested Nonlinear Regression Models. Oxford University Press, 2017. http://dx.doi.org/10.1093/oso/9780198505044.003.0015.

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Stepwise fitting of nonlinear nested regression models is considered in this chapter. The forward stepwise method of linear model building is used as far as possible. With linear models this is straightforward as there is in principle a free choice of the order that individual terms or factors are selected for inclusion. The only real issue is that sufficient submodels are examined to ensure that those finally selected really are amongst the best. The nonlinear case is not so straightforward, as embeddedness and parameter indeterminacy issues impose restrictions on the order in which steps can be taken to build a valid model, as certain parameters can only be meaningfully included if other specific parameters are definitely present. A systematic way of building valid nonlinear models of increasing complexity is described and illustrated by two examples using real data. A brief review of non-nested model building is also given.

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11

Väliaho, Hannu, and Timo Pekkonen. Procedure for Stepwise Regression Analysis : (with a Program in FORTRAN V). de Gruyter GmbH, Walter, 2022.

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12

Robertson, Rob. Effects of collinearity, sample size, multiple correlation, and predictor-criterion correlation salience on the order of variable entry in stepwise regression. 1997.

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13

Martin, Jeffrey J. Doing Research. Oxford University Press, 2017. http://dx.doi.org/10.1093/oso/9780190638054.003.0005.

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Researchers have to consider a host of factors when planning their research and analyzing their data. This chapter discusses a number of important research considerations. For instance, when planning research it is important to have a large enough sample to prevent conducting an underpowered study that would be unable to detect true differences when they existed. When selecting measures, researchers should understand exactly what they are assessing and determine if the scales used have a history of producing valid and reliable scores with similar samples. When developing measures, researchers should avoid the jingle jangle fallacy and avoid creating scales that are redundant with already developed scales or use names that obfuscate the reader. When analyzing their data scientists should avoid dichotomizing continuous constructs and should shun stepwise regression techniques. When compiling findings, researchers need to consider if their results are meaningful, so effect sizes should be reported and interpreted in light of absolute standards and relative to prior research.

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14

Lee, Patricia, Donald Stewart, and Stephen Clift. Group Singing and Quality of Life. Edited by Brydie-Leigh Bartleet and Lee Higgins. Oxford University Press, 2018. http://dx.doi.org/10.1093/oxfordhb/9780190219505.013.22.

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International research has broadly reported positive effects of singing on health. Choral singing, a social activity, can contribute to health and social and emotional well-being through enhancing individual and social variables, such as a sense of motivation, personal worth, concentration, and social engagement. This cross-sectional study aimed to establish a quantitative model to explain how multiple attributes of choral singing interact to impact on different dimensions of health and well-being. Using data from an Australian subsample within a multinational project, the results, from a series of stepwise hierarchical regression models, showed that choral singing benefited the choir members’ physical and psychological health and well-being through social engagement and a sense of positive identity. Choral singing also impacted social health and well-being positively by promoting feelings of excitement and importance to life, as well as longer duration of involvement in the choir. This study will contribute to developing targeted group singing or social activities to promote continued physical, psychological, and social health.

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15

Zoccali, Carmine, Davide Bolignano, and Francesca Mallamaci. Left ventricular hypertrophy in chronic kidney disease. Edited by David J. Goldsmith. Oxford University Press, 2018. http://dx.doi.org/10.1093/med/9780199592548.003.0107_update_001.

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Alterations in left ventricular (LV) mass and geometry and LV dysfunction increase in prevalence from stage 2 to stage 5 in CKD. Nuclear magnetic resonance is the most accurate and precise technique for measuring LV mass and function in patients with heart disease. Quantitative echocardiography is still the most frequently used means of evaluating abnormalities in LV mass and function in CKD. Anatomically, myocardial hypertrophy can be classified as concentric or eccentric. In concentric hypertrophy, the muscular component of the LV (LV wall) predominates over the cavity component (LV volume). Due to the higher thickness and myocardial fibrosis in patients with concentric LVH, ventricular compliance is reduced and the end-diastolic volume is small and insufficient to maintain cardiac output under varying physiological demands (diastolic dysfunction). In those with eccentric hypertrophy, tensile stress elongates myocardiocytes and increases LV end-diastolic volume. The LV walls are relatively thinner and with reduced ability to contract (systolic dysfunction). LVH prevalence increases stepwisely as renal function deteriorates and 70–80% of patients with kidney failure present with established LVH which is of the concentric type in the majority. Volume overload and severe anaemia are, on the other hand, the major drivers of eccentric LVH. Even though LVH may regress after renal transplantation, the prevalence of LVH after transplantation remains close to that found in dialysis patients and a functioning renal graft should not be seen as a guarantee of LVH regression. The vast majority of studies on cardiomyopathy in CKD are observational in nature and the number of controlled clinical trials in these patients is very small. Beta-blockers (carvedilol) and angiotensin receptors blockers improve LV performance and reduce mortality in kidney failure patients with LV dysfunction. Although current guidelines recommend implantable cardioverter-defibrillators in patients with ejection fraction less than 30%, mild to moderate symptoms of heart failure, and a life expectancy of more than 1 year, these devices are rarely offered to eligible CKD patients. Conversion to nocturnal dialysis and to frequent dialysis schedules produces a marked improvement in LVH in patients on dialysis. More frequent and/or longer dialysis are recommended in dialysis patients with asymptomatic or symptomatic LV disorders if the organizational and financial resources are available.

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