I plan to apply multinomial logistic regression using the complex sample option of SPSS. The dependent variables have 04 categories (low, moderate, high, and very high), and 05 independent variables are classified/categorized as Yes/no. The 'low' category of dependent variable will be the reference. 'No' will be the reference category of each independent variable.
To Perform Multinomial Logistic Regression Using Complex Samples in SPSS:
1. Set Up Complex Sample Design:
- Analyze > Complex Samples > Prepare for Analysis.
- Define your sampling plan (strata, clusters, weights).
2. Run Multinomial Logistic Regression:
- Analyze > Complex Samples > Logistic Regression.
- Move the dependent variable to the Dependent box.
- Move the independent variables to the Covariates box.
- Click Model to set 'low' as the reference category for the dependent variable.
- Set 'No' as the reference category for independent variables.
3. Specify Output Options:
- Click Statistics and check Odds Ratios and Confidence Intervals.
- Ensure P-values are selected.
4. Run the Analysis:
- Click OK to generate the results with p-values, odds ratios, and 95% CIs.
Gabriel Ezenri I don't find any option to select p-value. Kindly guide me.
Lingkan Barua Step-by-Step Guide:
1. Prepare the Complex Sample Design:
- Go to Analyze > Complex Samples > Prepare for Analysis.
- Define your sampling design by specifying the strata, clusters, and weights as necessary.
- Save the design.
2. Run Multinomial Logistic Regression:
- Go to Analyze > Complex Samples > Logistic Regression.
- Select your previously defined sample design from the list.
- Move your dependent variable to the Dependent box.
- Move your independent variables to the Covariates box.
- Click Model:
- In the Model dialog, set the reference category for the dependent variable to 'low'.
- Set the reference category for each independent variable to 'No'.
- Click Options (if available) or ensure that by default, the results will include the necessary statistics.
3. Run the Analysis:
- Click OK to run the analysis.
- SPSS will generate an output table that includes p-values, odds ratios, and 95% confidence intervals for each independent variable.
Example:
1. Set Up Design:
- Analyze > Complex Samples > Prepare for Analysis.
- Define strata, clusters, and weights.
2. Multinomial Logistic Regression:
- Analyze > Complex Samples > Logistic Regression.
- Choose your design.
- Set the dependent variable and covariates.
- Set 'low' as the reference category for the dependent variable.
- Set 'No' as the reference for each independent variable.
3. Ensure Output Includes Required Statistics:
- By default, SPSS will include p-values, odds ratios, and confidence intervals in the output.
4. Run and Interpret:
- Click OK to generate the results.
- Review the output for p-values, odds ratios, and 95% CIs.
This ensures you obtain the required statistics from the multinomial logistic regression using the complex samples module in SPSS.
Gabriel Ezenri The procedures you described is well known to me. But the problem is it does not give Odds ratio and corresponding p-value. It only give odds ratio.
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