Literature DB >> 20467520

Regression analysis for prediction: understanding the process.

Phillip B Palmer1, Dennis G O'Connell.   

Abstract

Research related to cardiorespiratory fitness often uses regression analysis in order to predict cardiorespiratory status or future outcomes. Reading these studies can be tedious and difficult unless the reader has a thorough understanding of the processes used in the analysis. This feature seeks to "simplify" the process of regression analysis for prediction in order to help readers understand this type of study more easily. Examples of the use of this statistical technique are provided in order to facilitate better understanding.

Entities:  

Year:  2009        PMID： 20467520      PMCID： PMC2845248     

Source DB:  PubMed          Journal:  Cardiopulm Phys Ther J        ISSN： 1541-7891


  6 in total

1.  Alternative approach to maximal exercise testing and VO2 max prediction in college students.

Authors:  J D George
Journal:  Res Q Exerc Sport       Date:  1996-12       Impact factor: 2.500

2.  Non-exercise VO2max estimation for physically active college students.

Authors:  J D George; W J Stone; L N Burkett
Journal:  Med Sci Sports Exerc       Date:  1997-03       Impact factor: 5.411

3.  An accurate VO2max nonexercise regression model for 18-65-year-old adults.

Authors:  Danielle I Bradshaw; James D George; Annette Hyde; Michael J LaMonte; Pat R Vehrs; Ronald L Hager; Frank G Yanowitz
Journal:  Res Q Exerc Sport       Date:  2005-12       Impact factor: 2.500

4.  PRESS-related statistics: regression tools for cross-validation and case diagnostics.

Authors:  D B Holiday; J E Ballard; B C McKeown
Journal:  Med Sci Sports Exerc       Date:  1995-04       Impact factor: 5.411

5.  Nonexercise regression models to estimate peak oxygen consumption.

Authors:  D P Heil; P S Freedson; L E Ahlquist; J Price; J M Rippe
Journal:  Med Sci Sports Exerc       Date:  1995-04       Impact factor: 5.411

Review 6.  Behind the scenes of cardiopulmonary exercise testing.

Authors:  R J Zeballos; I M Weisman
Journal:  Clin Chest Med       Date:  1994-06       Impact factor: 2.878
  6 in total
  10 in total

1.  Predictors of Overweight and Obesity in American Indian Families With Young Children.

Authors:  Alexandra K Adams; Emily J Tomayko; Kate A Cronin; Ronald J Prince; Kyungmann Kim; Lakeesha Carmichael; Tassy Parker
Journal:  J Nutr Educ Behav       Date:  2018-09-18       Impact factor: 3.045

2.  Self-management and blood pressure control in China: a community-based multicentre cross-sectional study.

Authors:  Zhan Qu; Monica Parry; Fang Liu; Xiulin Wen; Jieqiong Li; Yanan Zhang; Duolao Wang; Xiaomei Li
Journal:  BMJ Open       Date:  2019-03-20       Impact factor: 2.692

3.  Development of a novel linear model for predicting recipient's post-transplant serum creatinine level after living donor kidney transplantation: A multicenter cross-validation study.

Authors:  Jinsoo Rhu; Sung Joo Kim; Kyo Won Lee; Jae Berm Park; Kyunga Kim; Heejin Yoo; Hyejin Mo; Chanjoong Choi; Sang-Il Min; Jongwon Ha
Journal:  PLoS One       Date:  2019-04-18       Impact factor: 3.240

4.  What do international health electives and state examination scores have in common? - A cohort study to compare the results of written medical licensing examinations with the participation in international health electives during the final year of undergraduate medical education in Germany.

Authors:  Sylvère Störmann; Matthias W Angstwurm
Journal:  GMS J Med Educ       Date:  2018-11-30

5.  Prediction of the Wingate anaerobic mechanical power outputs from a maximal incremental cardiopulmonary exercise stress test using machine-learning approach.

Authors:  Efrat Leopold; Dalya Navot-Mintzer; Eyal Shargal; Sharon Tsuk; Tamir Tuller; Mickey Scheinowitz
Journal:  PLoS One       Date:  2019-03-12       Impact factor: 3.240

6.  Do nuclear magnetic resonance (NMR)-based metabolomics improve the prediction of pregnancy-related disorders? Findings from a UK birth cohort with independent validation.

Authors:  Nancy McBride; Paul Yousefi; Sara L White; Lucilla Poston; Diane Farrar; Naveed Sattar; Scott M Nelson; John Wright; Dan Mason; Matthew Suderman; Caroline Relton; Deborah A Lawlor
Journal:  BMC Med       Date:  2020-11-23       Impact factor: 8.775

7.  Left atrial acceleration factor as a magnetic resonance 4D flow measure of mean pulmonary artery wedge pressure in pulmonary hypertension.

Authors:  Gert Reiter; Gabor Kovacs; Clemens Reiter; Albrecht Schmidt; Michael Fuchsjäger; Horst Olschewski; Ursula Reiter
Journal:  Front Cardiovasc Med       Date:  2022-08-03

8.  Cardiodynamic variables measured by impedance cardiography during a 6-minute walk test are reliable predictors of peak oxygen consumption in young healthy adults.

Authors:  Fang Liu; Raymond C C Tsang; Alice Y M Jones; Mingchao Zhou; Kaiwen Xue; Miaoling Chen; Yulong Wang
Journal:  PLoS One       Date:  2021-05-25       Impact factor: 3.240

9.  Hypertension: development of a prediction model to adjust self-reported hypertension prevalence at the community level.

Authors:  Graciela Mentz; Amy J Schulz; Bhramar Mukherjee; Trivellore E Ragunathan; Denise White Perkins; Barbara A Israel
Journal:  BMC Health Serv Res       Date:  2012-09-11       Impact factor: 2.655

10.  Development and Optimization of Dispersible Tablet of Bacopa monnieri with Improved Functionality for Memory Enhancement.

Authors:  Vaishali Tejas Thakkar; Amol Deshmukh; Lal Hingorani; Payal Juneja; Lalji Baldaniya; Asha Patel; Tosha Pandya; Mukesh Gohel
Journal:  J Pharm Bioallied Sci       Date:  2017 Jul-Sep
  10 in total

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