Chapter 1
Introduction

• Home
• Chapters
  • 1 Introduction
  • 2 Statistical models
  • 3 One categorical covariate
  • 4 One quantitative covariate
  • 5 Multiple regression, the linear predictor
  • 6 Model building: From purpose to conclusion
  • 7 Alternative outcome types and link functions
  • 8 Further topics
  • A Appendix: Notation
  • B Appendix: Use of logarithms
  • C Appendix: Some recommendations
  • D Programming in R, SAS and STATA.
• Data examples
  • Birth Weight
  • Cardiac Output
  • CSL
  • Fatty Acids
  • Fever in Pregnancy
  • Fibrosis
  • Melanoma
  • Pbc 3
  • Surgery
  • Tetrahymena
  • Tryptase, study 1
  • Tryptase, study 2
  • Tryptase, study 3
  • Vitamin D
• Errata
• Links

Programs related to chapter 1:

Table 1.1.1: R-source SAS-source Stata-source
Table 1.1.2: R-source SAS-source Stata-source
Figure 1.1.1: R-source SAS-source Stata-source
Figure 1.2.1: R-source SAS-source Stata-source
Figure 1.2.2: R-source SAS-source Stata-source
Figure 1.3.3: R-source
Table 1.3.1: R-source SAS-source Stata-source
Figure 1.3.4: R-source SAS-source Stata-source
Figure 1.3.5:	See book, this figure contains no data analysis.
Table 1.3.2: R-source SAS-source Stata-source
Figure 1.3.6: R-source SAS-source Stata-source
Figure 1.3.7: R-source SAS-source Stata-source
Table 1.4.1:
Table 1.4.2: R-source SAS-source
Figure 1.4.1: R-source SAS-source
Table 1.5.1: R-source SAS-source
Figure 1.5.1: R-source SAS-source
Figure 1.5.2: R-source SAS-source
Table 1.5.2: R-source SAS-source
Figure 1.5.3: R-source SAS-source
Figure 1.5.4: R-source SAS-source
Table 1.5.3: R-source SAS-source
Table 1.5.4: R-source SAS-source
Figure 1.5.5: R-source SAS-source
Figure 1.5.6: R-source SAS-source
Table 1.6.1:	See book, this table involves no data analysis.
Table 1.6.2:	See book, this table involves no data analysis.

Lerchedahl & Graversen