Statistical Method Selection

Help me select and justify appropriate statistical methods for my research data.

**Research Question**: [RESEARCH QUESTION]
**Data Description**:
- Sample size: [n]
- Dependent variable(s): [DV, measurement level: nominal / ordinal / interval / ratio]
- Independent variable(s) / predictors: [IV, measurement level and categories]
- Data structure: [independent groups / paired samples / longitudinal / hierarchical]
- Study design: [cross-sectional / longitudinal / experimental]

Please conduct the following analysis:

1. **Assumption Testing**: Which statistical assumptions need to be checked before the main analysis (normality, homogeneity of variance, independence, linearity, etc.)?

2. **Method Recommendation**: Which analysis method(s) are most appropriate for this data configuration? Justify your recommendation and mention alternatives.

3. **Effect Sizes**: Which effect size measures should be reported and how should they be interpreted?

4. **Handling Missing Data**: Which strategy do you recommend (listwise deletion, multiple imputation, FIML)?

5. **Software Recommendation**: Which software (R, SPSS, Python, Stata) is suitable for the recommended analyses, and which packages or procedures should be used?

6. **Reporting Standards**: How should results be reported according to APA standards?

Replace placeholders in [square brackets]: [RESEARCH QUESTION][DV, measurement level: nominal / ordinal / interval / ratio][IV, measurement level and categories][cross-sectional / longitudinal / experimental]