Data example: Surgery

• 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

Surgery

An investigation conducted by Berg et al. (1997) included 691 patients
undergoing either orthopedic, gynecological or abdominal surgery.

The main purpose of the study was to determine whether some types of
neuromuscular blocking agents (NBA) were more prone to complications
than others. Furthermore, it was of interest to know whether residual
neuromuscular block (RNB, here quantified by the TOF-ratio, a
measure of neuromuscular function) was a mediating risk factor in this
connection.

Variable list:

age: Age of the patient

surgtype: Type of surgery
        1: Orthopedic
        2: Gynecological
        3: Abdominal

blocking: Neuromuscular blocking agent
        1: Pancuronium
        2: Vecuronium
        3: Atracurium

longact: Is the blocking agent long-acting?
        0: No
        1: Yes

duration: Duration of the operation in minutes

tofratio: The ratio of T4/T1 in a train-of-four stimulation

complication: Does the patient experience a pulmonary complication?
        0: No
        1: Yes

The dataset

Data for Surgery

Scripts for loading the dataset

• Load data in R
• Load data in Stata
• Load data in SAS

Programs related to Surgery

Table 1.5.1: R-source SAS-source (tab-surgery-ch1-pres)
Table 3.1.7: R-source SAS-source (tab-surgery-ch3-pres)
Table 3.1.9: R-source SAS-source (tab-surgery-ch3-indcl)
Table 3.1.10: R-source SAS-source (tab-surgery-ch3-approx-cl)
Table 3.1.11: R-source SAS-source (tab-surgery-ch3-ci)
Table 3.1.13: R-source SAS-source (tab-surgery-ch3-expected-calc)
Table 3.2.10: R-source SAS-source (tab-surgery-ch3-pres3)
Table 3.2.11: R-source SAS-source (tab-surgery-ch3-exp)
Table 3.2.12: R-source SAS-source (tab-surgery-ch3-or)
Table 6.2.8: R-source SAS-source (tab-ch6surgery-comp-nba)
Table 6.2.9: R-source SAS-source (tab-ch6surgery-nba)
Table 6.2.10: R-source SAS-source (tab-ch6surgery-results-model1)
Figure 6.2.9: R-source SAS-source (fig-ch6-berg-reschi-age)
Table 6.2.11: R-source SAS-source (tab-ch6surgery-results-model3)
Table 6.2.12: R-source SAS-source (tab-ch6blocking-estimates-or)
Table 6.2.13: R-source SAS-source (tab-ch6surgery-results-model4)
Figure 6.2.10: R-source SAS-source (fig-ch6-berg-residual-plots)
Table 6.2.14: R-source SAS-source (tab-ch6-surgery-gof)
Figure 6.2.11: R-source (fig-ch6-berg-influence-compl)
Table 6.2.15: R-source SAS-source (tab-ch6surgery-results-final)
Figure 6.2.12: R-source SAS-source (fig-ch6-berg-fit)

Lerchedahl & Graversen