### Abstract

Language | English |
---|---|

Pages | 40-43 |

Number of pages | 4 |

Volume | 12 |

Specialist publication | Microbiologist |

Publication status | Published - Jun 2011 |

### Fingerprint

### Keywords

- variables
- regression equation
- stepwise multiple regression procedure
- stepwise multiple regression
- influence of climatic variables
- growth
- crustose lichen Rhizocarpon geographicum (L.)DC

### Cite this

*Microbiologist*,

*12*, 40-43.

}

*Microbiologist*, vol. 12, pp. 40-43.

**Statnote 25: Stepwise multiple regression.** / Hilton, Anthony; Armstrong, Richard A.

Research output: Contribution to specialist publication › Article

TY - GEN

T1 - Statnote 25: Stepwise multiple regression

AU - Hilton, Anthony

AU - Armstrong, Richard A.

PY - 2011/6

Y1 - 2011/6

N2 - An investigator may also wish to select a small subset of the X variables which give the best prediction of the Y variable. In this case, the question is how many variables should the regression equation include? One method would be to calculate the regression of Y on every subset of the X variables and choose the subset that gives the smallest mean square deviation from the regression. Most investigators, however, prefer to use a ‘stepwise multiple regression’ procedure. There are two forms of this analysis called the ‘step-up’ (or ‘forward’) method and the ‘step-down’ (or ‘backward’) method. This Statnote illustrates the use of stepwise multiple regression with reference to the scenario introduced in Statnote 24, viz., the influence of climatic variables on the growth of the crustose lichen Rhizocarpon geographicum (L.)DC.

AB - An investigator may also wish to select a small subset of the X variables which give the best prediction of the Y variable. In this case, the question is how many variables should the regression equation include? One method would be to calculate the regression of Y on every subset of the X variables and choose the subset that gives the smallest mean square deviation from the regression. Most investigators, however, prefer to use a ‘stepwise multiple regression’ procedure. There are two forms of this analysis called the ‘step-up’ (or ‘forward’) method and the ‘step-down’ (or ‘backward’) method. This Statnote illustrates the use of stepwise multiple regression with reference to the scenario introduced in Statnote 24, viz., the influence of climatic variables on the growth of the crustose lichen Rhizocarpon geographicum (L.)DC.

KW - variables

KW - regression equation

KW - stepwise multiple regression procedure

KW - stepwise multiple regression

KW - influence of climatic variables

KW - growth

KW - crustose lichen Rhizocarpon geographicum (L.)DC

UR - http://issuu.com/societyforappliedmicrobiology/docs/june2011_micro

M3 - Article

VL - 12

SP - 40

EP - 43

JO - Microbiologist

T2 - Microbiologist

JF - Microbiologist

SN - 1479-2699

ER -