Pendahuluan: Perbandingan waktu pada model survival dan model runtun waktu

Summary

This video discusses the differences between survival analysis and time series analysis, focusing on the role of time in both. While time is measured in both analyses, the contexts differ: time series analysis examines measurements over time (e.g., stock prices, passenger counts) with dependencies between time points, while survival analysis treats time as a target variable, often representing event occurrences like death, recovery, or equipment failure. The video also explores how time in survival analysis can be explained through survival functions or hazard functions, highlighting its role in modeling event timings.

Takeaways

• 😀 The script discusses the difference between time studied in Survival Analysis and Time Series Analysis, highlighting the confusion often found between the two despite both focusing on time.
• 😀 Time in Survival Analysis is not just an index but a target variable, with the focus on analyzing events that happen at specific time points.
• 😀 In Time Series Analysis, the time variable is an index, and measurements are taken at each point in time, such as passenger counts or currency exchange rates.
• 😀 A key example given is the number of passengers on a flight over the years, where time is the index and the passenger count is measured at each time point.
• 😀 Time Series Analysis deals with measurements that depend on prior time points, often showing closed dependencies, such as past values influencing future outcomes.
• 😀 Survival Analysis, on the other hand, centers on time as the response or target variable, analyzing events like recovery, death, or failure over time.
• 😀 Time in Survival Analysis is explained by various factors, and it can be represented through functions like the Survival Function or Hazard Function.
• 😀 The focus in Survival Analysis is to measure how long an event takes to occur and the factors influencing its timing, such as health recovery or machinery failure.
• 😀 Survival Analysis involves looking at events like recovery, death, or bankruptcy and analyzing the time at which these events occur.
• 😀 Mathematical models in Survival Analysis focus on time as the response, with various factors explaining how quickly or slowly events happen over time.

Q & A

What is the main focus of the discussion in the transcript?

The main focus is to explain the difference between survival analysis time and time series analysis time, specifically how time is used in each type of analysis.

How is time treated in survival analysis?

In survival analysis, time is considered as a target variable, which is measured in relation to events such as recovery, death, bankruptcy, or equipment failure.

What is the role of time in time series analysis?

In time series analysis, time functions as an index or a continuous measurement point at which data is recorded, such as the number of passengers on a flight or currency exchange rates over time.

What kind of data is typically used in time series analysis?

Time series analysis typically uses data that is measured at regular intervals, such as stock prices, harvest yields, or the number of passengers over a certain period.

How is the relationship between time and data modeled in time series analysis?

In time series analysis, the data at a given time point is usually dependent on previous data points, often modeled with a closed-loop relationship.

What is the key distinction between survival analysis and time series analysis in terms of time?

The key distinction is that in survival analysis, time is the target variable that is explained by other factors, while in time series analysis, time serves as the index or variable for measuring other outcomes.

What are some examples of events studied in survival analysis?

Examples of events studied in survival analysis include recovery, death, equipment failure, or bankruptcy, which are measured over time.

What mathematical tools are used to analyze time in survival analysis?

In survival analysis, mathematical tools like survival functions and hazard functions are used to represent and analyze the time until an event occurs.

What are the differences between time as an index and time as a target variable?

When time is an index, it is used as a point for measuring other variables. When time is a target variable, it is the outcome of interest that is influenced by various factors.

Why might time be represented differently in survival analysis and time series analysis?

Time is represented differently because in survival analysis, it is a dependent outcome that can be influenced by various factors, while in time series analysis, it is an independent variable used for indexing measurements.