Podcast
Questions and Answers
What is the primary function of the aes function in ggplot?
What is the primary function of the aes function in ggplot?
- To map variables to aesthetics (correct)
- To specify the data frame
- To create a bar chart
- To calculate summary statistics
What does the after_stat function do in ggplot?
What does the after_stat function do in ggplot?
- It calculates the mean of the data
- It creates a new aesthetic mapping
- It removes missing values from the data
- It computes a statistic after the data has been processed (correct)
What is the purpose of the theme_bw function in ggplot?
What is the purpose of the theme_bw function in ggplot?
- To add a title to the plot
- To change the color scheme of the plot
- To modify the axis labels
- To create a black and white theme for the plot (correct)
What is the result of the code count(continent) %>% mutate(perc = n/sum(n) * 100)?
What is the result of the code count(continent) %>% mutate(perc = n/sum(n) * 100)?
What does the scale_colour_grey function do in ggplot?
What does the scale_colour_grey function do in ggplot?
What is the purpose of the group = 1 argument in the geom_bar function?
What is the purpose of the group = 1 argument in the geom_bar function?
What is the result of the code gapminder2 %>% count(continent)?
What is the result of the code gapminder2 %>% count(continent)?
What is the purpose of the mutate function in the code gapminder2 %>% count(continent) %>% mutate(perc = n/sum(n) * 100)?
What is the purpose of the mutate function in the code gapminder2 %>% count(continent) %>% mutate(perc = n/sum(n) * 100)?
What is the purpose of removing observations with missing values for the variable cat_fbs?
What is the purpose of removing observations with missing values for the variable cat_fbs?
What is the result of the code count(cat_fbs)?
What is the result of the code count(cat_fbs)?
Flashcards
aes function in ggplot
aes function in ggplot
Maps variables to aesthetics (visual properties) in a ggplot2 plot.
after_stat function
after_stat function
Calculates statistics after ggplot2 has processed the data.
theme_bw function
theme_bw function
Creates a black and white theme for ggplot2 plots.
count(continent) %>% mutate(perc = ...)
count(continent) %>% mutate(perc = ...)
Signup and view all the flashcards
scale_colour_grey function
scale_colour_grey function
Signup and view all the flashcards
group = 1 in geom_bar
group = 1 in geom_bar
Signup and view all the flashcards
gapminder2 %>% count(continent)
gapminder2 %>% count(continent)
Signup and view all the flashcards
mutate function purpose
mutate function purpose
Signup and view all the flashcards
removing missing values (cat_fbs)
removing missing values (cat_fbs)
Signup and view all the flashcards
count(cat_fbs)
count(cat_fbs)
Signup and view all the flashcards
Study Notes
Survival Analysis
- Survival analysis is also known as duration analysis or time-to-event analysis.
- It's useful in follow-up studies where participants or patients are followed up until they develop the event of interest.
- Examples of such studies include retrospective cohort or prospective cohort studies.
- Survival analysis can be applied to any study that involves both the duration of follow-up and the event of interest.
Types of Survival Analysis
- There are three main types of survival analysis:
- Non-parametric survival analysis (e.g. Kaplan-Meier estimates)
- Semi-parametric survival analysis (e.g. Cox proportional hazards regression)
- Parametric survival analysis (e.g. Weibull parametric survival analysis)
Kaplan-Meier Estimates
- Kaplan-Meier estimates are used in non-parametric survival analysis.
- They are often performed at the beginning of an analysis to understand the trend of survival probabilities.
Cox Proportional Hazards (PH) Regression
- Cox PH regression is a type of semi-parametric survival analysis.
- It can be used for simple (univariable) or multiple (multivariable) regression analysis.
R Studio Project
- It is recommended to start a new analysis project by creating a new RStudio project.
Data Visualization
- ggplot can be used to create plots, such as bar charts and histograms.
- The y-axis can be adjusted to show proportions by using the
after_statfunction.
Studying That Suits You
Use AI to generate personalized quizzes and flashcards to suit your learning preferences.
