Statistical notes for clinical researchers: simple linear regression 3 – residual analysis

Statistical notes for clinical researchers: simple linear regression 3 – residual analysis

초록

In the previous sections, simple linear regression (SLR) 1 and 2, we developed a SLR model and evaluated its predictability. To obtain the best fitted line the intercept and slope were calculated by using the least square method. Predictability of the model was assessed by the proportion of the explained variability among the total variation of the response variable. In this session, we will discuss four basic assumptions of regression models for justification of the estimated regression model and residual analysis to check them.

제목
Statistical notes for clinical researchers: simple linear regression 3 – residual analysis
제목 (타언어)
Statistical notes for clinical researchers: simple linear regression 3 – residual analysis
저자
Hae-Young Kim
DOI
10.5395/rde.2019.44.e11
발행일
2019
저널명
Restorative Dentistry and Endodontics
44
1
페이지
1 ~ 8