Objective: Analyze the factors influencing the duration of employment (EmploymentDuration) among participants using survival analysis techniques. Assumption: Assume that the dataset includes: • EmploymentDuration: Time until the participant exits their current employment (in months). Event: Indicator of whether the employment exit event has occurred (1 for event, for censored). Tasks: 1. Data Preparation: • Load the statsnew.csv dataset, including Employment Duration and Event. . Check for missing values and handle them appropriately. • Convert categorical variables into suitable numerical formats. 2. Exploratory Data Analysis: Visualize the distribution of Employment Duration using Kaplan-Meier curves stratified by key predictors (e.g., Education Level, Gender). . Estimate and plot the Kaplan-Meier survival estimates for different groups. 3. Cox Proportional Hazards Model: • • • Fit a Cox proportional hazards model with Employment Duration as the time variable and Event as the event indicator. Include predictors such as Age, Gender, EducationLevel, Income, HoursWorked, JobSatisfaction, Marital Status, etc. Assess the proportional hazards assumption using Schoenfeld residuals and graphical diagnostics. 4. Model Refinement: . • Address any violations of the proportional hazards assumption by incorporating time- dependent covariates or stratification. Perform variable selection using stepwise methods based on AIC.

These question need to be solved using R with the given data, please do not provide AI solution , also i need detailed solution , do everything in detail which is required, answer it as soon as possible.