BTS 510 Lab 7

set.seed(12345)
library(tidyverse)

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✔ lubridate 1.9.4     ✔ tidyr     1.3.1
✔ purrr     1.0.4     
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library(Stat2Data)
theme_set(theme_classic(base_size = 16))

1 Learning objectives

• Add predictors to a linear regression model
• Interpret partial regression coefficients
• Re-code predictors to answer your research questions
• Compare different models using R^2_{change}

2 Data

• ICU data from the Stat2Data package
  • ID: Patient ID code
  • Survive: 1 = patient survived to discharge or 0 = patient died
  • Age: Age (in years)
  • AgeGroup: 1 = young (under 50), 2 = middle (50-69), 3 = old (70+)
  • Sex: 1 = female or 0 = male
  • Infection: 1 = infection suspected or 0 = no infection
  • SysBP: Systolic blood pressure (in mm of Hg)
  • Pulse: Heart rate (beats per minute)
  • Emergency: 1 = emergency admission or 0 = elective admission

3 Research question

How do infection status (Infection) and admission type (Emergency) predict blood pressure?

4 Tasks

1. Conduct three linear regression models to address the above research questions.

• Model 1: Infection status predicts blood pressure
• Model 2: Admission type predicts blood pressure
• Model 3: Infection status and admission type predict blood pressure

2. Which is the best model?

• Use the F-test for R^2_{change} and the AIC values to help you decide. Report the tests and values that you used to decide this.

3. Report the results of the best model, including:

• Intercept value, test statistic, p-value, interpretation (in words)
• Slope value(s), test statistic(s), p-value(s), interpretation(s) (in words)
• R^2 value, test statistic, p-value, interpretation (in words)

4. Based on model 3, what are the predicted blood pressures for the 4 combinations of infection status and admission type? (i.e., infected non-emergency, non-infected non-emergency, infected emergency, non-infected non-emergency)

5. Using the predicted and residual values, assess whether the assumptions are met for model 3. Include the plots and describe your conclusions based on them.

6. In plain language, answer the research question: How do infection status and admission type predict blood pressure? (This should not be lengthy – just a couple sentences.)