Conducting regression analysis involves several steps:
Data Collection: Gather relevant data through surveys, clinical trials, or other observational studies. Model Selection: Choose the appropriate type of regression model based on the nature of the dependent variable and the research question. Variable Selection: Identify the independent variables to be included in the model. This may involve statistical techniques like stepwise selection or theoretical considerations. Model Fitting: Use statistical software to fit the regression model to the data. Model Validation: Assess the model's performance using validation techniques such as cross-validation or bootstrapping. Interpretation: Analyze the results to make informed conclusions about the relationships between variables.
