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NAVAL POSTGRADUATE SCHOOL MONTEREY, CALIFORNIATHESIS EXPLORATORY SURVIVAL ANALYSIS OF DEPARTMENT OF DEFENSE BLUE-COLLAR AND WHITE-COLLAR CIVILIAN EMPLOYEE ATTRITION FACTORS by Anthony C. French March
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01
Step 1: Collect the necessary data, including the survival time and status of individuals.
02
Step 2: Clean the data by removing any missing or invalid values.
03
Step 3: Determine the time interval for the analysis, such as monthly or yearly intervals.
04
Step 4: Calculate the survival probabilities at each time point using Kaplan-Meier estimation.
05
Step 5: Plot the survival curve to visualize the overall survival trend over time.
06
Step 6: Conduct hypothesis tests, such as log-rank test, to compare survival curves between different groups.
07
Step 7: Explore the impact of different factors on survival by using Cox proportional hazards regression.
08
Step 8: Interpret the results and draw conclusions about the factors influencing survival.

Who needs exploratory survival analysis of?

01
Researchers in medical and healthcare fields who want to assess the survival outcomes of patients.
02
Pharmaceutical companies conducting clinical trials to evaluate the efficacy of a new treatment.
03
Public health officials analyzing survival rates for specific diseases or conditions.
04
Insurance companies determining life expectancy for policyholders.
05
Epidemiologists studying the survival patterns in a population.
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Exploratory survival analysis is a statistical approach used to analyze time-to-event data, helping to understand the duration until one or more events occur, such as failure or death.
Typically, researchers or organizations conducting studies that involve time-to-event data analysis may be required to file exploratory survival analysis if mandated by regulatory authorities or study protocols.
Filling out exploratory survival analysis involves collecting appropriate time-to-event data, defining the events of interest, conducting statistical testing and modeling, and documenting the findings and methodology used.
The purpose of exploratory survival analysis is to uncover patterns, trends, and factors affecting the time until an event occurs, aiding in decision-making and hypothesis generation.
Information to report includes the data used, methods of analysis, key findings, estimates of survival functions, and any relevant covariates or confounding variables.
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