Example

Scenario Overview

• Task: Analyze factors predicting victim status among students to enhance campus safety.

• Data: Collected on demographics, activities, social networks, and past victimization experiences.

Research Question

• Explore the relationship between gender and victim status for sexual assault.

Variables of Interest

• Victim Status: 0 (Not victim), 1 (Victim)

• Gender: 0 (Male), 1 (Female)

Statistical Analysis Summary

• Analysis of 110 observations:

  • Males: 85.07% non-victims, 14.93% victims

  • Females: 37.21% non-victims, 62.79% victims

  • Overall: 66.36% non-victims, 33.64% victims

Logistic Regression Types

• Binary Logistic Regression: Two categories

• Multinomial Logistic Regression: More than two categories

• Ordinal Logistic Regression: Ordered categories

Logistic Regression Output (Gender Only)

• Model Results:

  • Coefficient (Gender): 2.2637

  • p-value: 0.0000 (statistically significant)

  • Odds Ratio (Gender): 9.6188 (female students are more likely to be victims)

• Model Fit: Chi-Square = -27.2562, df = 1, p-value = 0.0000

Additional Factors Considered

• Age Group Analysis:

  • Under 25: 0

  • Over 25: 1

• Logistic regression including age:

  • Gender Coefficient: 2.2026, p-value: 0.0000

  • Age Group Coefficient: -1.0577, p-value: 0.0276

Final Findings

• Significant relationship identified:

  • Females significantly more likely to be victims (OR = 9.05, 95% CI [3.54, 23.11], p <.001).

  • Students aged 25+ significantly less likely to be victims (OR = 0.35, 95% CI [0.14, 0.88], p <.001).